{
 "cells": [
  {
   "cell_type": "code",
   "id": "initial_id",
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "end_time": "2025-04-20T03:56:45.011357Z",
     "start_time": "2025-04-20T03:56:44.819650Z"
    }
   },
   "source": [
    "import json\n",
    "import os\n",
    "import warnings\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "\n",
    "warnings.filterwarnings(\"ignore\", category=FutureWarning)"
   ],
   "outputs": [],
   "execution_count": 1
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-20T03:56:45.016133Z",
     "start_time": "2025-04-20T03:56:45.011357Z"
    }
   },
   "cell_type": "code",
   "source": [
    "data_dir = os.path.join(os.getcwd(), \"data\")\n",
    "data_10_dir = os.path.join(data_dir, \"10G_data\")\n",
    "data_30_dir = os.path.join(data_dir, \"30G_data\")"
   ],
   "id": "1849b90e0eb66552",
   "outputs": [],
   "execution_count": 2
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-20T03:56:45.022428Z",
     "start_time": "2025-04-20T03:56:45.016133Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import functools\n",
    "import time\n",
    "def timer(func):\n",
    "    @functools.wraps(func)\n",
    "    def wrapper(*args, **kwargs):\n",
    "        t0 = time.perf_counter()\n",
    "        res = func(*args, **kwargs)\n",
    "        t1 = time.perf_counter()\n",
    "        if t1 - t0 > 1:\n",
    "            print(f\"{func.__name__} took {t1 - t0:.2f}s to execute.\")\n",
    "        else:\n",
    "            print(f\"{func.__name__} took {(t1 - t0) * 1000:.2f}ms to execute.\")\n",
    "        return res\n",
    "\n",
    "    return wrapper"
   ],
   "id": "662e99ac45fae8ea",
   "outputs": [],
   "execution_count": 3
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-20T04:09:28.567574Z",
     "start_time": "2025-04-20T03:56:45.022428Z"
    }
   },
   "cell_type": "code",
   "source": [
    "@timer\n",
    "def load_data(dir):\n",
    "    total_len, data = 0, []\n",
    "    for file in os.listdir(dir):\n",
    "        if file.endswith('.parquet'):\n",
    "            d = pd.read_parquet(os.path.join(dir, file))\n",
    "            total_len += len(d)\n",
    "            data.append(d.drop_duplicates())\n",
    "    print(f\"Loaded {total_len} rows from {dir}.\")\n",
    "    data = pd.concat(data, ignore_index=True)\n",
    "    data.drop_duplicates(inplace=True)\n",
    "    return data\n",
    "if not os.path.exists(os.path.join(data_dir, \"data_30G.parquet\")):\n",
    "    data = load_data(data_30_dir)\n",
    "    data.to_parquet(os.path.join(data_dir, \"data_30G.parquet\"), index=False)\n",
    "else:\n",
    "    data = pd.read_parquet(os.path.join(data_dir, \"data_30G.parquet\"))\n",
    "print(f\"Remain {len(data)} rows.\")"
   ],
   "id": "72763210c4b3e3cf",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loaded 300000000 rows from F:\\研究生学业\\结课作业\\研一下\\数据挖掘\\个人作业\\互评作业1\\code\\data\\30G_data.\n",
      "load_data took 759.54s to execute.\n",
      "Remain 2400000 rows.\n"
     ]
    }
   ],
   "execution_count": 4
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-20T04:09:28.691411Z",
     "start_time": "2025-04-20T04:09:28.567574Z"
    }
   },
   "cell_type": "code",
   "source": "data.head()",
   "id": "4ec5246fc6a9c33b",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "   id                  timestamp   user_name chinese_name  \\\n",
       "0   1  2025-01-09T01:38:20+00:00     UZPFPZJ           彭敏   \n",
       "1   2  2023-07-08T22:53:52+00:00       UEHSG           高杰   \n",
       "2   3  2023-12-31T20:00:57+00:00    fxuujvnk          姜子轩   \n",
       "3   4  2023-03-22T11:12:02+00:00      DDERCI           梁云   \n",
       "4   5  2024-08-10T11:43:08+00:00  RTABMQKQLG           钱俊   \n",
       "\n",
       "                  email  age    income gender country  \\\n",
       "0       xtnlkqsb@qq.com   36   73000.0      女     俄罗斯   \n",
       "1  rkpktrqz@outlook.com   58  223000.0      女      巴西   \n",
       "2  vwnquvla@outlook.com   88  858000.0      男      美国   \n",
       "3       jpajekzz@qq.com   61  485000.0      男      德国   \n",
       "4      haqlhpmb@163.com   33  437000.0      男      中国   \n",
       "\n",
       "           chinese_address                                   purchase_history  \\\n",
       "0  广西壮族自治区绍兴和谐路152号2单元1384  {\"average_price\":15.940000000000001,\"category\"...   \n",
       "1     黑龙江省大连建设路127号1单元1835  {\"average_price\":563.4100000000001,\"category\":...   \n",
       "2       浙江省厦门繁荣路15号5单元1442  {\"average_price\":669.34,\"category\":\"书籍\",\"items...   \n",
       "3       四川省宁波上海路30号6单元2134  {\"average_price\":637.66,\"category\":\"书籍\",\"items...   \n",
       "4       四川省成都康乐路181号6单元391  {\"average_price\":505.0,\"category\":\"家居\",\"items\"...   \n",
       "\n",
       "   is_active registration_date  credit_score  phone_number  \n",
       "0      False        2024-10-02           423  918-668-7857  \n",
       "1      False        2021-03-19           567  205-503-3300  \n",
       "2      False        2022-05-07           767  673-105-7503  \n",
       "3      False        2020-07-08           587  387-482-7104  \n",
       "4      False        2023-10-12           404  602-478-3001  "
      ],
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>user_name</th>\n",
       "      <th>chinese_name</th>\n",
       "      <th>email</th>\n",
       "      <th>age</th>\n",
       "      <th>income</th>\n",
       "      <th>gender</th>\n",
       "      <th>country</th>\n",
       "      <th>chinese_address</th>\n",
       "      <th>purchase_history</th>\n",
       "      <th>is_active</th>\n",
       "      <th>registration_date</th>\n",
       "      <th>credit_score</th>\n",
       "      <th>phone_number</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2025-01-09T01:38:20+00:00</td>\n",
       "      <td>UZPFPZJ</td>\n",
       "      <td>彭敏</td>\n",
       "      <td>xtnlkqsb@qq.com</td>\n",
       "      <td>36</td>\n",
       "      <td>73000.0</td>\n",
       "      <td>女</td>\n",
       "      <td>俄罗斯</td>\n",
       "      <td>广西壮族自治区绍兴和谐路152号2单元1384</td>\n",
       "      <td>{\"average_price\":15.940000000000001,\"category\"...</td>\n",
       "      <td>False</td>\n",
       "      <td>2024-10-02</td>\n",
       "      <td>423</td>\n",
       "      <td>918-668-7857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2023-07-08T22:53:52+00:00</td>\n",
       "      <td>UEHSG</td>\n",
       "      <td>高杰</td>\n",
       "      <td>rkpktrqz@outlook.com</td>\n",
       "      <td>58</td>\n",
       "      <td>223000.0</td>\n",
       "      <td>女</td>\n",
       "      <td>巴西</td>\n",
       "      <td>黑龙江省大连建设路127号1单元1835</td>\n",
       "      <td>{\"average_price\":563.4100000000001,\"category\":...</td>\n",
       "      <td>False</td>\n",
       "      <td>2021-03-19</td>\n",
       "      <td>567</td>\n",
       "      <td>205-503-3300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2023-12-31T20:00:57+00:00</td>\n",
       "      <td>fxuujvnk</td>\n",
       "      <td>姜子轩</td>\n",
       "      <td>vwnquvla@outlook.com</td>\n",
       "      <td>88</td>\n",
       "      <td>858000.0</td>\n",
       "      <td>男</td>\n",
       "      <td>美国</td>\n",
       "      <td>浙江省厦门繁荣路15号5单元1442</td>\n",
       "      <td>{\"average_price\":669.34,\"category\":\"书籍\",\"items...</td>\n",
       "      <td>False</td>\n",
       "      <td>2022-05-07</td>\n",
       "      <td>767</td>\n",
       "      <td>673-105-7503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2023-03-22T11:12:02+00:00</td>\n",
       "      <td>DDERCI</td>\n",
       "      <td>梁云</td>\n",
       "      <td>jpajekzz@qq.com</td>\n",
       "      <td>61</td>\n",
       "      <td>485000.0</td>\n",
       "      <td>男</td>\n",
       "      <td>德国</td>\n",
       "      <td>四川省宁波上海路30号6单元2134</td>\n",
       "      <td>{\"average_price\":637.66,\"category\":\"书籍\",\"items...</td>\n",
       "      <td>False</td>\n",
       "      <td>2020-07-08</td>\n",
       "      <td>587</td>\n",
       "      <td>387-482-7104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2024-08-10T11:43:08+00:00</td>\n",
       "      <td>RTABMQKQLG</td>\n",
       "      <td>钱俊</td>\n",
       "      <td>haqlhpmb@163.com</td>\n",
       "      <td>33</td>\n",
       "      <td>437000.0</td>\n",
       "      <td>男</td>\n",
       "      <td>中国</td>\n",
       "      <td>四川省成都康乐路181号6单元391</td>\n",
       "      <td>{\"average_price\":505.0,\"category\":\"家居\",\"items\"...</td>\n",
       "      <td>False</td>\n",
       "      <td>2023-10-12</td>\n",
       "      <td>404</td>\n",
       "      <td>602-478-3001</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 5
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-20T04:09:34.164621Z",
     "start_time": "2025-04-20T04:09:28.691411Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# 删除注册时间晚于记录时间的数据\n",
    "data.timestamp = pd.to_datetime(data.timestamp, utc=True)\n",
    "data.registration_date = pd.to_datetime(data.registration_date, utc=True)\n",
    "invalid_rows = data[data.timestamp < data.registration_date]\n",
    "print(len(invalid_rows))\n",
    "data = data[data.timestamp >= data.registration_date]\n",
    "print(len(data))"
   ],
   "id": "39910d0787ee168b",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1232\n",
      "2398768\n"
     ]
    }
   ],
   "execution_count": 6
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-20T04:09:34.452889Z",
     "start_time": "2025-04-20T04:09:34.164621Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# 删除低价值列\n",
    "data.drop(['id', 'timestamp', 'email', 'country', 'chinese_address',\n",
    "           'is_active', 'phone_number', 'registration_date'], axis=1, inplace=True)\n",
    "data.head()"
   ],
   "id": "7c5675e40dc113ee",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "    user_name chinese_name  age    income gender  \\\n",
       "0     UZPFPZJ           彭敏   36   73000.0      女   \n",
       "1       UEHSG           高杰   58  223000.0      女   \n",
       "2    fxuujvnk          姜子轩   88  858000.0      男   \n",
       "3      DDERCI           梁云   61  485000.0      男   \n",
       "4  RTABMQKQLG           钱俊   33  437000.0      男   \n",
       "\n",
       "                                    purchase_history  credit_score  \n",
       "0  {\"average_price\":15.940000000000001,\"category\"...           423  \n",
       "1  {\"average_price\":563.4100000000001,\"category\":...           567  \n",
       "2  {\"average_price\":669.34,\"category\":\"书籍\",\"items...           767  \n",
       "3  {\"average_price\":637.66,\"category\":\"书籍\",\"items...           587  \n",
       "4  {\"average_price\":505.0,\"category\":\"家居\",\"items\"...           404  "
      ],
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_name</th>\n",
       "      <th>chinese_name</th>\n",
       "      <th>age</th>\n",
       "      <th>income</th>\n",
       "      <th>gender</th>\n",
       "      <th>purchase_history</th>\n",
       "      <th>credit_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>UZPFPZJ</td>\n",
       "      <td>彭敏</td>\n",
       "      <td>36</td>\n",
       "      <td>73000.0</td>\n",
       "      <td>女</td>\n",
       "      <td>{\"average_price\":15.940000000000001,\"category\"...</td>\n",
       "      <td>423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>UEHSG</td>\n",
       "      <td>高杰</td>\n",
       "      <td>58</td>\n",
       "      <td>223000.0</td>\n",
       "      <td>女</td>\n",
       "      <td>{\"average_price\":563.4100000000001,\"category\":...</td>\n",
       "      <td>567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>fxuujvnk</td>\n",
       "      <td>姜子轩</td>\n",
       "      <td>88</td>\n",
       "      <td>858000.0</td>\n",
       "      <td>男</td>\n",
       "      <td>{\"average_price\":669.34,\"category\":\"书籍\",\"items...</td>\n",
       "      <td>767</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>DDERCI</td>\n",
       "      <td>梁云</td>\n",
       "      <td>61</td>\n",
       "      <td>485000.0</td>\n",
       "      <td>男</td>\n",
       "      <td>{\"average_price\":637.66,\"category\":\"书籍\",\"items...</td>\n",
       "      <td>587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>RTABMQKQLG</td>\n",
       "      <td>钱俊</td>\n",
       "      <td>33</td>\n",
       "      <td>437000.0</td>\n",
       "      <td>男</td>\n",
       "      <td>{\"average_price\":505.0,\"category\":\"家居\",\"items\"...</td>\n",
       "      <td>404</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 7
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-20T04:09:46.881282Z",
     "start_time": "2025-04-20T04:09:34.452889Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# 简化购物记录\n",
    "purchase_history = data.purchase_history.apply(\n",
    "    lambda x: ((y := json.loads(x))['average_price'], len(y['items'])))\n",
    "data['price'] = purchase_history.apply(lambda x: x[0]*x[1])\n",
    "data['items'] = purchase_history.apply(lambda x: x[1]).astype(int)\n",
    "data.drop(['purchase_history'], axis=1, inplace=True)\n",
    "data.head()"
   ],
   "id": "d45267d63075cdb",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "    user_name chinese_name  age    income gender  credit_score    price  items\n",
       "0     UZPFPZJ           彭敏   36   73000.0      女           423   159.40     10\n",
       "1       UEHSG           高杰   58  223000.0      女           567  2253.64      4\n",
       "2    fxuujvnk          姜子轩   88  858000.0      男           767  2677.36      4\n",
       "3      DDERCI           梁云   61  485000.0      男           587  6376.60     10\n",
       "4  RTABMQKQLG           钱俊   33  437000.0      男           404  4545.00      9"
      ],
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       "    .dataframe tbody tr th {\n",
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       "        text-align: right;\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_name</th>\n",
       "      <th>chinese_name</th>\n",
       "      <th>age</th>\n",
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       "      <th>0</th>\n",
       "      <td>UZPFPZJ</td>\n",
       "      <td>彭敏</td>\n",
       "      <td>36</td>\n",
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       "      <td>女</td>\n",
       "      <td>423</td>\n",
       "      <td>159.40</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>UEHSG</td>\n",
       "      <td>高杰</td>\n",
       "      <td>58</td>\n",
       "      <td>223000.0</td>\n",
       "      <td>女</td>\n",
       "      <td>567</td>\n",
       "      <td>2253.64</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>fxuujvnk</td>\n",
       "      <td>姜子轩</td>\n",
       "      <td>88</td>\n",
       "      <td>858000.0</td>\n",
       "      <td>男</td>\n",
       "      <td>767</td>\n",
       "      <td>2677.36</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>DDERCI</td>\n",
       "      <td>梁云</td>\n",
       "      <td>61</td>\n",
       "      <td>485000.0</td>\n",
       "      <td>男</td>\n",
       "      <td>587</td>\n",
       "      <td>6376.60</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>RTABMQKQLG</td>\n",
       "      <td>钱俊</td>\n",
       "      <td>33</td>\n",
       "      <td>437000.0</td>\n",
       "      <td>男</td>\n",
       "      <td>404</td>\n",
       "      <td>4545.00</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 8
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-20T04:09:46.890629Z",
     "start_time": "2025-04-20T04:09:46.881282Z"
    }
   },
   "cell_type": "code",
   "source": [
    "def set_outlier_anomaly(df, columns=None, method='IQR', set_value=np.nan, set_tag=False):\n",
    "    \"\"\"\n",
    "        找到指定数据列中的离群点并设置为空值。\n",
    "        set_tag = True时，增加anomaly列将异常值标记为3。\n",
    "    \"\"\"\n",
    "    # 如果没有指定列，默认为所有数值列\n",
    "    if columns is None:\n",
    "        columns = df.select_dtypes(include=[np.number]).columns\n",
    "    columns = [col for col in columns if col not in [\"alarm_code\", \"max_alarm_lvl\", \"anomaly\"]]\n",
    "\n",
    "    for column in columns:\n",
    "        if method == '3-sigma':\n",
    "            # 使用3-sigma方法判断异常值\n",
    "            mean = df[column].mean()\n",
    "            std = df[column].std()\n",
    "            is_outlier = (df[column] - mean).abs() > 3 * std\n",
    "\n",
    "        elif method == 'IQR':\n",
    "            # 使用IQR方法判断异常值\n",
    "            Q1 = df[column].quantile(0.25)\n",
    "            Q3 = df[column].quantile(0.75)\n",
    "            IQR = Q3 - Q1\n",
    "            is_outlier = (df[column] < Q1 - 1.5 * IQR) | (df[column] > Q3 + 1.5 * IQR)\n",
    "\n",
    "        else:\n",
    "            raise ValueError(\"Unsupported method. Use '3-sigma' or 'IQR'.\")\n",
    "\n",
    "        if set_value is not None:\n",
    "            df.loc[is_outlier, column] = set_value\n",
    "        if set_tag:\n",
    "            if 'anomaly' not in df.columns:\n",
    "                df['anomaly'] = 0\n",
    "            df.loc[is_outlier, 'anomaly'] = 3\n",
    "\n",
    "    return df\n",
    "# data = set_outlier_anomaly(data, set_value=None, set_tag=True)\n",
    "# data[data['anomaly']==3]"
   ],
   "id": "ed971d87ff1808bd",
   "outputs": [],
   "execution_count": 9
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-20T04:09:50.668814Z",
     "start_time": "2025-04-20T04:09:46.890629Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# 设置支持中文字体\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']  # 中文黑体\n",
    "plt.rcParams['axes.unicode_minus'] = False     # 正常显示负号\n",
    "\n",
    "# 年龄分布直方图\n",
    "sns.histplot(data['age'], bins=83)\n",
    "plt.title(\"年龄分布\")\n",
    "plt.show()\n",
    "\n",
    "# 收入分布直方图\n",
    "sns.histplot(data['income'])\n",
    "plt.title(\"收入分布\")\n",
    "plt.show()"
   ],
   "id": "87b3b9c15011bd50",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/png": 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pyMjIBvuioqIUFRXVYF9sbOyVKg8AALQTpgtBANqHr85WqNzlrtfeNayDunW6KgAVAYA3QhAAvyh3uTVr7YF67b8YNYAQ1A40FHJbGnAJzmhthCCLaOkByx8HvNbmyza0h+1tSFvaB5wQza2hkNvSgEtwvjIC/dxtSwhBbZgvP+gtPWD544DX2hrahrmjv9XgidZdVaNn1x/yamtr29sQX9bRl7EN/Sy6q2queK1N1dBafAlnZghyrXlCtNtsKvryTL32QJ+AzbAOLeWv431b+sXIHwhBbUDHrj1U/JVTNnl/sq0tnajNehA6W1GlBf9XWK/9Z8P7B6Catquhg2573Ye+hDMzBLmW/gLT2HO3oZDb2POpNbe3sUB+6bHSDHX5cvzz1y+i/vjl0KzH+4YQgkzm0h8ejzw6pxBlv3NQl366vy2dZHw5GTT2BAoNduhcpfc3A/vy23dLX5loTVfiIOKPV2ca+02/NfdtQzU09LPRWHtjY7uGdVDXjt5fq+OPfdiYlv7c+0tjz91AH3/q7i+PPKrpdOGXxcoqT70Ttb9qbc1X4xvir+djS385bOxn5tJw5ZFHHbsG9lscCEEB0tSJuu4T2OORMoc1/NH/hpjhJNXSE0dTB91Ln5i+/PZtpoN2XQ2d5Br7zbWh39AaO6k3dB8t3QdX4pWzhn5GfTmpN1RDQz8bjbU3Nnbu6G/pH67zxsnUJptP+7Ch7Wrs576xsQ2teUP1NvabenP3Y2PHicZ+FluqpWvekLrPc49HcjqdCg8P17R7Wu953tJg09J1MMMr2b783F9ar8cjTR3S8J+9aS2EoADx14m6pU+KK/Eqii9vjfjyBPLHfF/4csAKDXZ4nUxr62ruSa6x/eVrADCjhrahoZN6a79yd7aiStkbC42Tqc3m2z5sbG1aOra586Xmn4CbOk60pC5fHs8Ma97cVxV9CWy+/CLa2uvgDy39WQ40QhC8+BLOrsSrTv44GfjrCejbAStas/MPGSdTf9bVUmZ49bCtH0jNojV/KWgpX9bcX9vV3F8qmrpGpjn3WXu/MB9CkIW19MDCk719YB3bj/YaJgO9Xe3hOWKGX3bMiBBkYYE+sAAAWkd7CHL+YA90AQAAAIFACAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJZECAIAAJYUkBC0efNmpaSk6Oabb9bo0aNVUlIiScrKylJ0dLTxb9iwYcacw4cPKy0tTQkJCcrOzpbH4zH6du3apXvvvVeJiYlatmyZ12Nt3LhRQ4YMUVJSktatW9c6GwgAAEyv1UPQ0aNH9dRTTykzM1Pbtm1T3759NWPGDEnSJ598oldeeUW7d+/W7t279fbbb0uS3G630tPTNWDAAOXl5amkpERr1qyRJJWXl+uxxx7TiBEjtHLlSuXn52vnzp2SLgSnqVOnKiMjQ0uXLtWiRYtUWlra2psMAABMqNVDUElJiTIzM/Xd735X1157rcaOHatDhw6pqqpKxcXFio+PV+fOndW5c2eFh4dLkrZt2yan06np06erd+/emjJlinJzcyVJa9euVffu3TVp0iT17dtXGRkZRt/q1auVmJioMWPGKDo6WuPHj9c777zT2psMAABMKKi1H3DIkCFetz/99FP16dNHhw8fVk1NjVJTU3X8+HElJCRo7ty5uv7661VYWKi4uDiFhoZKkqKjo4230IqKipSYmCibzSZJio2N1fPPPy9JKiws1J133mk8VmxsrF566SWfa66urr6sbW2KRx7VeUfPu6due+0Nj0ce2Zoe22ibL2NbOt8MY81QV21X3XUzQ12Bfixz11X/+WaOutrDvvVrXXXWzVR1+X1sG6/r4g1/nGObe5+tHoLqcrvdWrZsmR555BEdOXJEN954o2bOnKkuXbroueee08yZM7V06VI5nU716tXLmGez2WS323X69Gk5nU7169fP6AsPD9eJEyckSS6Xy2te3T5f7N+/vwVb2bCaTj3kdDrrtVdVVzfY7nS5mjW2sfnNHdvS+WYYa5a6JO91M0tdZt1fpqjr4nrV/tc0dbWHfdsKdTldLlPW5a+x7aEuyT/n2OYKaAh68cUXFRoaqjFjxig4OFijRo0y+mbNmqWUlBQ5nU45HA516NDBa25ISIgqKirq9dW2S2qyzxcxMTFyOBw+z2tK8VdO4+2+uoIcDu/2i0k5PCxMstmaHttImy9jWzrfDGPNUpfkvW5mqcus+8sUdYWFyelyGetmmrraw771Z10ej7FupqrLz2PbfF0Xz2/+OMdWV1c3K1wFLAQVFBTorbfe0qpVqxQcHFyv/5prrlFNTY1OnDihiIgIFRcXe/W7XC4FBwcrIiJC5eXl9dolNdnnC4fDccUXyCbbpZnm3z112o23UmwNjW9umy9jWzrfDGPNUFdtV90+M9QV6Mcyd11Gh7Fu5qirPexbf9ZV9zhpprr8P7Zt11W7bv44xzZXQD4iX1ZWpszMTD3zzDOKioqSJGVnZys/P98Ys3fvXtntdvXs2VMxMTHat2+f13y3262IiIh6fQcPHlSPHj0kqck+AABgba0egioqKpSenq6UlBQNGzZMLpdLLpdL0dHReuGFF1RQUKDt27dr1qxZSk1NVWhoqBISEuR0OpWXlydJWrx4sQYNGiSHw6Hk5GTt2bNHO3bsUGVlpZYsWaKkpCRJ0vDhw7V+/XoVFRXJ5XIpJyfH6AMAANbW6m+Hbd++XUeOHNGRI0e0atUqo33Lli367ne/q8cff1wOh0MjR47UlClTLhQZFKSsrCxlZmZqwYIFstvtysnJkSR17dpV06dP18SJE9WxY0d16tRJ8+fPlyT1799fEyZMUFpamkJCQtSnTx+NGzeutTcZAACYUKuHoKFDh6qoqKjBvszMTGVmZjbYl5KSok2bNunAgQOKi4tTly5djL6xY8cqKSlJpaWlio+PV1hYmNE3efJkjRw50vjY/aUXWAMAAGsK6KfDfNWtWzcNHjy4wb7IyEhFRkY22BcVFWVcewQAACDxBaoAAMCiCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSCEEAAMCSAhKCNm/erJSUFN18880aPXq0SkpKJEmHDx9WWlqaEhISlJ2dLY/HY8zZtWuX7r33XiUmJmrZsmVe97dx40YNGTJESUlJWrdunVffW2+9pUGDBiklJUUFBQX+3zgAANAmtHoIOnr0qJ566illZmZq27Zt6tu3r2bMmCG326309HQNGDBAeXl5Kikp0Zo1ayRJ5eXleuyxxzRixAitXLlS+fn52rlzp6QLwWnq1KnKyMjQ0qVLtWjRIpWWlkqS3nvvPWVnZ2vOnDlauHChnn76aZ06daq1NxkAAJhQq4egkpISZWZm6rvf/a6uvfZajR07VocOHdK2bdvkdDo1ffp09e7dW1OmTFFubq4kae3aterevbsmTZqkvn37KiMjw+hbvXq1EhMTNWbMGEVHR2v8+PF65513JEkrVqxQamqqhg4dqltuuUUpKSnavHlza28yAAAwoaDWfsAhQ4Z43f7000/Vp08fFRYWKi4uTqGhoZKk6Oho422yoqIiJSYmymazSZJiY2P1/PPPS5IKCwt15513GvcXGxurl156yeibOnWqV9/u3bs1ZswYn2qurq72cSu/nkce1Xm3z7unbnvtDY9HHtmaHttomy9jWzrfDGPNUFdtV911M0NdgX4sc9dV//lmjrraw771a1111s1Udfl9bBuv6+INf5xjm3ufrR6C6nK73Vq2bJkeeeQRHT16VL169TL6bDab7Ha7Tp8+LafTqX79+hl94eHhOnHihCTJ5XJ5zWtuny/279/v85yvU9Oph5xOZ732qurqBtudLlezxjY2v7ljWzrfDGPNUpfkvW5mqcus+8sUdV1cr9r/mqau9rBvW6Eup8tlyrr8NbY91CX55xzbXAENQS+++KJCQ0M1ZswYvfDCC+rQoYNXf0hIiCoqKuRwOLz6atslXXafL2JiYuRwOHye15Tir5wKDw+v1x7kcHi3X0zK4WFhks3W9NhG2nwZ29L5Zhhrlrok73UzS11m3V+mqCssTE6Xy1g309TVHvatP+vyeIx1M1Vdfh7b5uu6eH7zxzm2urq6WeEqYCGooKBAb731llatWqXg4GBFRESouLjYa4zL5TL6ysvL67VL+tq+uhdC1+3zhcPhuOILZJPt0kzz75467cZbKbaGxje3zZexLZ1vhrFmqKu2q26fGeoK9GOZuy6jw1g3c9TVHvatP+uqe5w0U13+H9u266pdN3+cY5srIB+RLysrU2Zmpp555hlFRUVJupAE9+3b5zXG7XYrIiKiXt/BgwfVo0ePBudd2rd3794G+wAAgLW1egiqqKhQenq6UlJSNGzYMLlcLrlcLsXHx8vpdCovL0+StHjxYg0aNEgOh0PJycnas2ePduzYocrKSi1ZskRJSUmSpOHDh2v9+vUqKiqSy+VSTk6OV9/y5ct1/PhxnTx5Urm5uUYfAACwtlZ/O2z79u06cuSIjhw5olWrVhntW7ZsUVZWljIzM7VgwQLZ7Xbl5ORIkrp27arp06dr4sSJ6tixozp16qT58+dLkvr3768JEyYoLS1NISEh6tOnj8aNGydJSk5O1saNG3X33XdLkm677Tbj/wEAgLW1eggaOnSoioqKGuzr1auXNm3apAMHDiguLk5dunQx+saOHaukpCSVlpYqPj5eYWFhRt/kyZM1cuRIHT9+XAkJCcbF0DabTQsXLtRDDz2kc+fOaeDAgcbH7AEAgLUF9NNhDenWrZsGDx7cYF9kZKQiIyMb7IuKijKuL7pUbGzslSoPAAC0E3yBKgAAsCRCEAAAsCRCEAAAsCRCEAAAsCRCEAAAsCRCEAAAsCRCEAAAsCRCEAAAsCRCEAAAsCRCEAAAsCRCEAAAsCRCEAAAsCRCEAAAsCRCEAAAsCRCEAAAsCRCEAAAsCRCEAAAsCRCEAAAsCRCEAAAsCRCEAAAsCRCEAAAsCRCEAAAsCRCEAAAsCRCEAAAsCRCEAAAsCRCEAAAsCRCEAAAsCRCEAAAsCRCEAAAsCRCEAAAsCRCEAAAsCRCEAAAsCRCEAAAsKTLCkGvvvqqKisrvdoKCgr0n//5n1ekKAAAAH+7rBD0q1/9SufPn/dqi4qK0r59+65ETQAAAH4X5Mvg3bt3S5I8Ho8+/PBDdezY0bj917/+Vd/4xjeufIUAAAB+4FMImjZtmiTJZrNp9uzZstlskiS73a4+ffpowYIFV75CAAAAP/ApBG3dulWS1L9/f+Xn5ys8PNwvRQEAAPjbZV0TlJSUpKAgn/ITAACAqVxWklmyZMmVrgMAAKBVXVYI2rx5s+bNm6djx44ZbR6PRzabTYcOHbpixQEAAPjLZYWgWbNm6fvf/77S0tIUHBx8pWsCAADwu8u+sOeBBx5QZGTklawFAACg1VzWhdE//elPNXfuXJ06depK1wMAANAqLuuVoLVr16q4uFhDhgzRN77xDa+Pyr/55ptXrDgAAAB/uawQ9P3vf/9K1wEAANCqLisEfe9737vSdQAAALSqywpB/fv3N74y41J8RB4AALQFl3Vh9JYtW7R582Zt3rxZ69at03PPPaeoqCg9//zzzb6P8vJyJScn67PPPjPasrKyFB0dbfwbNmyY0Xf48GGlpaUpISFB2dnZ8ng8Rt+uXbt07733KjExUcuWLfN6nI0bN2rIkCFKSkrSunXrLmdzAQBAO3RZIeiGG24w/vXr10+pqal644039Prrrzdrfnl5udLT0/X55597tX/yySd65ZVXtHv3bu3evVtvv/22JMntdis9PV0DBgxQXl6eSkpKtGbNGuO+HnvsMY0YMUIrV65Ufn6+du7cKelCcJo6daoyMjK0dOlSLVq0SKWlpZezyQAAoJ25rBDUkJCQEJ08ebJZY6dMmaL77rvPq62qqkrFxcWKj49X586d1blzZ+NTZ9u2bZPT6dT06dPVu3dvTZkyRbm5uZIufFKte/fumjRpkvr27auMjAyjb/Xq1UpMTNSYMWMUHR2t8ePH65133rlSmwwAANqwy7om6KGHHvK6Jsjj8ejIkSO6/fbbmzV/7ty5ioyM1LPPPmu0HT58WDU1NUpNTdXx48eVkJCguXPn6vrrr1dhYaHi4uIUGhoqSYqOjlZJSYkkqaioSImJiUY9sbGxxttyhYWFuvPOO43HiI2N1UsvveTz9lZXV/s85+t45FGdd/S8e+q2197weOTRpddhNXQfzbxfv803w1gz1FXbVXfdzFBXoB/L3HXVf76Zo672sG/9WleddTNVXX4f28brunjDH+fY5t7nFfmIvM1mU48ePXTrrbc2a35Df2n6yJEjuvHGGzVz5kx16dJFzz33nGbOnKmlS5fK6XSqV69eXo9nt9t1+vRpOZ1O9evXz+gLDw/XiRMnJEkul8trXt0+X+zfv9/nOV+nplMPOZ3Oeu1V1dUNtjtdrmaNbWx+c8e2dL4ZxpqlLsl73cxSl1n3lynqurhetf81TV3tYd+2Ql1Ol8uUdflrbHuoS/LPOba5WvQR+X/84x/64osvdMMNN6hr164tKmTUqFEaNWqUcXvWrFlKSUmR0+mUw+FQhw4dvMaHhISooqKiXl9tu6Qm+3wRExMjh8Ph87ymFH/l9Pojk7WCHA7v9otJOTwsTLrkE3n1xjbS5svYls43w1iz1CV5r5tZ6jLr/jJFXWFhcrpcxrqZpq72sG/9WZfHY6ybqery89g2X9fF85s/zrHV1dXNCleXFYKcTqemTZumrVu3Kjg4WJWVlRo2bJjmzZvX4IZfjmuuuUY1NTU6ceKEIiIiVFxc7NXvcrkUHBysiIgIlZeX12uX1GSfLxwOxxVfIJtsl2aaf/fUaTfeSrE1NL65bb6Mbel8M4w1Q121XXX7zFBXoB/L3HUZHca6maOu9rBv/VlX3eOkmery/9i2XVftuvnjHNtcl3Vh9OzZs1VTU6M///nP+vjjj/XnP/9ZVVVVmj179mUXkp2drfz8fOP23r17Zbfb1bNnT8XExGjfvn1GX1lZmdxutyIiIur1HTx4UD169JCkJvsAAIC1XVYIeu+99zRjxgwjUPTo0UPTp0/Xtm3bLruQ/v3764UXXlBBQYG2b9+uWbNmKTU1VaGhoUpISJDT6VReXp4kafHixRo0aJAcDoeSk5O1Z88e7dixQ5WVlVqyZImSkpIkScOHD9f69etVVFQkl8ulnJwcow8AAFjbZb0d1rNnT+3cuVP333+/0bZz505df/31l13I6NGjdeTIET3++ONyOBwaOXKkpkyZcqHIoCBlZWUpMzNTCxYskN1uV05OjiSpa9eumj59uiZOnKiOHTuqU6dOmj9/vqQLwWrChAlKS0tTSEiI+vTpo3Hjxl12jQAAoP24rBA0Y8YMTZw4URs2bFBkZKTKysq0Z88evfrqqz7dT1FRkdftzMxMZWZmNjg2JSVFmzZt0oEDBxQXF6cuXboYfWPHjlVSUpJKS0sVHx+vsLAwo2/y5MkaOXKk8bH7Sy+wBgAA1uTT22E1NTXau3evwsLCtGHDBg0cOFB//etflZCQoI0bNyo+Pt5fdUqSunXrpsGDB3sFoFqRkZG66667vAJQraioKN1+++0EIAAAYGh2CCoqKtI999yj9PR0vfvuu7ruuuv0ox/9SFdddZVeeeUVPfjggzpy5Ig/awUAALhimh2CZs6cqTFjxqigoECTJk0y2vPz87V7926NGDFCTz/9tF+KBAAAuNKaHYKKi4t1zz33yG6vP8XhcOgHP/hBvWt8AAAAzKrZIei2227TvHnzvP74YK1//etfevHFF3XLLbdc0eIAAAD8pdmfDps3b56mTZumO+64Q7169dI111wjh8OhM2fO6NNPP1W/fv3029/+1p+1AgAAXDHNDkFXX321Fi9erKNHj2rv3r06ceKEqqqq1LlzZ/Xv31+33HKL1zfLAwAAmJnPfyeod+/e6t27tz9qAQAAaDWX9bUZAAAAbR0hCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWBIhCAAAWFLAQlB5ebmSk5P12WefGW2HDx9WWlqaEhISlJ2dLY/HY/Tt2rVL9957rxITE7Vs2TKv+9q4caOGDBmipKQkrVu3zqvvrbfe0qBBg5SSkqKCggL/bhQAAGgzAhKCysvLlZ6ers8//9xoc7vdSk9P14ABA5SXl6eSkhKtWbPGGP/YY49pxIgRWrlypfLz87Vz505JF4LT1KlTlZGRoaVLl2rRokUqLS2VJL333nvKzs7WnDlztHDhQj399NM6depU628wAAAwnYCEoClTpui+++7zatu2bZucTqemT5+u3r17a8qUKcrNzZUkrV27Vt27d9ekSZPUt29fZWRkGH2rV69WYmKixowZo+joaI0fP17vvPOOJGnFihVKTU3V0KFDdcsttyglJUWbN29u3Y0FAACmFJAQNHfuXE2YMMGrrbCwUHFxcQoNDZUkRUdHq6SkRJJUVFSkxMRE2Ww2SVJsbKwOHDhgzLv11luN+/m6vk8++cTnequrq6/4P4888nhU758uaVftW4Ke+uMvHdtYmy9jWzrfDGPNUZfqrZs56jLr/jJHXcbiXVw3s9TVHvatP+fXXTcz1WXW/WWWumrXzR/n2OrqajVHULNGXWGRkZH12pxOp3r16mXcttlsstvtOn36tJxOp/r162f0hYeH68SJE5Ikl8vlNa+5fb7Yv3+/z3O+Tk2nHnI6nfXaq6qrG2x3ulzNGtvY/OaObel8M4w1S12S97qZpS6z7i9T1HVxvWr/a5q62sO+bYW6nC6XKevy19j2UJfkn3NscwUkBDXE4XCoQ4cOXm0hISGqqKio11fb3tC85vb5IiYmRg6Hw+d5TSn+yqnw8PB67UEOh3f7xaQcHhYmXXwlrNGxjbT5Mral880w1ix1Sd7rZpa6zLq/TFFXWJicLpexbqapqz3sW3/W5fEY62aquvw8ts3XdfH85o9zbHV1dbPClWlCUEREhIqLi73aXC6XgoODFRERofLy8nrttfOa6qt7IXTdPl84HI4rvkA22S7NNP/uqdPu0cUbtobGN7fNl7EtnW+GsWaoq7arbp8Z6gr0Y5m7LqPDWDdz1NUe9q0/66p7nDRTXf4f27brql03f5xjm8s0fycoJiZG+/btM26XlZXJ7XYrIiKiXt/BgwfVo0ePBudd2rd3794G+wAAgLWZJgQlJCTI6XQqLy9PkrR48WINGjRIDodDycnJ2rNnj3bs2KHKykotWbJESUlJkqThw4dr/fr1KioqksvlUk5Ojlff8uXLdfz4cZ08eVK5ublGHwAAsDbTvB0WFBSkrKwsZWZmasGCBbLb7crJyZEkde3aVdOnT9fEiRPVsWNHderUSfPnz5ck9e/fXxMmTFBaWppCQkLUp08fjRs3TpKUnJysjRs36u6775Yk3Xbbbcb/AwAAawtoCCoqKvK6nZKSok2bNunAgQOKi4tTly5djL6xY8cqKSlJpaWlio+PV1hYmNE3efJkjRw5UsePH1dCQoJxMbTNZtPChQv10EMP6dy5cxo4cKDxMXsAAGBtpnklqFa3bt00ePDgBvsiIyMb/Hi9JEVFRSkqKqrBvtjY2CtVHgAAaCdMc00QAABAayIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASzJdCMrKylJ0dLTxb9iwYZKkw4cPKy0tTQkJCcrOzpbH4zHm7Nq1S/fee68SExO1bNkyr/vbuHGjhgwZoqSkJK1bt65VtwUAAJiX6ULQJ598oldeeUW7d+/W7t279fbbb8vtdis9PV0DBgxQXl6eSkpKtGbNGklSeXm5HnvsMY0YMUIrV65Ufn6+du7cKelCcJo6daoyMjK0dOlSLVq0SKWlpYHcPAAAYBKmCkFVVVUqLi5WfHy8OnfurM6dOys8PFzbtm2T0+nU9OnT1bt3b02ZMkW5ubmSpLVr16p79+6aNGmS+vbtq4yMDKNv9erVSkxM1JgxYxQdHa3x48frnXfeCeQmAgAAkwgKdAF1HT58WDU1NUpNTdXx48eVkJCguXPnqrCwUHFxcQoNDZUkRUdHq6SkRJJUVFSkxMRE2Ww2SVJsbKyef/55SVJhYaHuvPNO4/5jY2P10ksv+VxXdXV1SzetHo88qvOOnndP3fbaGx6PPLI1PbbRNl/GtnS+Gcaaoa7arrrrZoa6Av1Y5q6r/vPNHHW1h33r17rqrJup6vL72DZe18Ub/jjHNvc+TRWCjhw5ohtvvFEzZ85Uly5d9Nxzz2nmzJm66aab1KtXL2OczWaT3W7X6dOn5XQ61a9fP6MvPDxcJ06ckCS5XC6veXX7fLF///4WbFXDajr1kNPprNdeVV3dYLvT5WrW2MbmN3dsS+ebYaxZ6pK8180sdZl1f5mirovrVftf09TVHvZtK9TldLlMWZe/xraHuiT/nGOby1QhaNSoURo1apRxe9asWUpJSVG/fv3UoUMHr7EhISGqqKiQw+Hw6qttl9Rkny9iYmLkcDh8nteU4q+cCg8Pr9ce5HB4t19MyuFhYZLN1vTYRtp8GdvS+WYYa5a6JO91M0tdZt1fpqgrLExOl8tYN9PU1R72rT/r8niMdTNVXX4e2+brunh+88c5trq6ulnhylQh6FLXXHONampqdO2116q4uNirz+VyKTg4WBERESovL6/XLqnJPl84HI4rvkA22S7NNP/uqdNuvJVia2h8c9t8GdvS+WYYa4a6arvq9pmhrkA/lrnrMjqMdTNHXe1h3/qzrrrHSTPV5f+xbbuu2nXzxzm2uUx1YXR2drby8/ON23v37pXdbld0dLT27dtntJeVlcntdisiIkIxMTFefQcPHlSPHj0kqck+AABgbaYKQf3799cLL7yggoICbd++XbNmzVJqaqpuv/12OZ1O5eXlSZIWL16sQYMGyeFwKDk5WXv27NGOHTtUWVmpJUuWKCkpSZI0fPhwrV+/XkVFRXK5XMrJyTH6AACAtZnq7bDRo0fryJEjevzxx+VwODRy5EhNmTJFQUFBysrKUmZmphYsWCC73a6cnBxJUteuXTV9+nRNnDhRHTt2VKdOnTR//nxJF0LVhAkTlJaWppCQEPXp00fjxo0L5CYCAACTMFUIkqTMzExlZmbWa09JSdGmTZt04MABxcXFqUuXLkbf2LFjlZSUpNLSUsXHxyssLMzomzx5skaOHGl85P7SC6wBAIA1mS4ENaVbt24aPHhwg32RkZGKjIxssC8qKkpRUVF+rAwAALQ1promCAAAoLUQggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCURggAAgCVZIgQdPnxYaWlpSkhIUHZ2tjweT6BLAgAAAdbuQ5Db7VZ6eroGDBigvLw8lZSUaM2aNYEuCwAABFi7D0Hbtm2T0+nU9OnT1bt3b02ZMkW5ubmBLgsAAARYUKAL8LfCwkLFxcUpNDRUkhQdHa2SkpJmza1928ztdsvhcFzRumpqqhVsa+Ax67V7JE+NOtg8ks32NWMbbvNlbEvnm2GsOeqqUYhDXutmjrrMur/MUVcHm8dr3cxSV3vYt/6t69/rZq66/Du27dd14fzmj3NsdXX1hUf4mstfbJ52foHM/Pnzdf78ec2aNctou/XWW/V///d/ioiIaHKu2+3W/v37/V0iAADwg5iYGHXo0KHR/nb/SpDD4ai3A0JCQlRRUfG1ISgoKEgxMTGy2+2y2RqItQAAwHQ8Ho9qamoUFNR0zGn3ISgiIkLFxcVebS6XS8HBwV871263N5kgAQBA29XuL4yOiYnRvn37jNtlZWVyu91f+yoQAABo39p9CEpISJDT6VReXp4kafHixRo0aNAVvwgLAAC0Le3+wmhJ2rJlizIzMxUSEiK73a6cnBxFRUUFuiwAABBAlghBkvTVV1/pwIEDiouLU5cuXQJdDgAACDDLhCAAAIC62v01QQAAAA0hBAEAAEsiBJnM5s2blZKSoptvvlmjR482vuLj8OHDSktLU0JCgrKzs7/2T4EjcB599FHjS3p37dqle++9V4mJiVq2bFmAK0NjFi5cqPT0dOM2zzdzW716te666y7FxcXpoYceUllZmSTWzYzKy8uVnJyszz77zGhrap1a+5hJCDKRo0eP6qmnnlJmZqa2bdumvn37asaMGXK73UpPT9eAAQOUl5enkpIS4yQLc1m7dq22b98u6cKT/7HHHtOIESO0cuVK5efna+fOnQGuEJcqLCzU8uXLNWPGDEni+WZyR48e1UsvvaSXX35ZGzZsUGRkpH7+85+zbiZUXl6u9PR0ff7550ZbU+sUkGOmB6axdetWz//+7/8atwsKCjyxsbGeTZs2eRISEjz/+te/PB6Px3Po0CHPgw8+GKgy0YhTp055Bg0a5Bk+fLgnLy/Ps2zZMs8999zjqamp8Xg8Hs+mTZs8mZmZAa4SdVVXV3vGjBnjeeGFF4w2nm/mtmHDBs8TTzxh3P7ggw88t99+O+tmQg8//LDnjTfe8Hzzm9/0lJWVeTyepp9fgThm8kqQiQwZMkQ/+MEPjNuffvqp+vTpo8LCQsXFxSk0NFSSFB0dbbxNBvPIzs7W0KFD9e1vf1uSVFRUpMTERON752JjY3XgwIEAVohLrVixQocPH9YNN9ygLVu2yO1283wzuaioKO3cuVOHDh3S2bNntXz5ct1+++2smwnNnTtXEyZM8Gprap0CccwkBJmU2+3WsmXL9OCDD8rpdKpXr15Gn81mk91u1+nTpwNYIerauXOnCgoK9OSTTxptl65beHi4Tpw4EYjy0ACXy6UXX3xRkZGR+uKLL/T6669r3LhxPN9MLioqSsOHD1dqaqri4+O1b98+TZs2jXUzocjIyHptTa1TII6ZhCCTevHFFxUaGqoxY8bI4XDU+yLXkJAQVVRUBKg61HX+/HnNmjVLs2fPVnh4uNF+6bqxZuayadMmnTt3Tm+88YaeeOIJLVu2TC6XS3l5eTzfTOzjjz/Wu+++q1WrVumDDz7Qfffdpx/+8IccJ9uIptYpEMdMQpAJFRQU6K233tLzzz+v4OBgRUREqLy83GuMy+VScHBwgCpEXS+//LK+9a1vafDgwV7tl64ba2YuX375peLi4tS1a1dJUlBQkKKjo3XmzBmebya2bt06jRgxQnFxcerUqZN++tOfqqysjONkG9HUOgXimBnk13uHz8rKypSZmalnnnnG+H6zmJgYrV692muM2+1WREREoMpEHfn5+Tp16pTi4+MlSRUVFdqwYYMk6Tvf+Y4x7uDBg+rRo0dAakR91113nc6fP+/V9sUXX+ipp57S73//e6ON55u51NTU6NSpU8Ztl8ulc+fOKSgoSPv27TPaWTdzaup8FhMTo3Xr1hl9rXHM5JUgE6moqFB6erpSUlI0bNgwuVwuuVwuxcfHy+l0Ki8vT5K0ePFiDRo0SA6HI8AVQ5KWL1+u/Px8/eEPf9Af/vAHJScn64knntC7776rPXv2aMeOHaqsrNSSJUuUlJQU6HJx0V133aUjR45oxYoV+vLLL/Xmm2+qsLBQd999N883E4uPj9emTZv0+uuvKz8/XxkZGerWrZseeugh1q0NSEhIaHSdkpOTW/2YyXeHmcjmzZs1adKkeu1btmxRUVGRMjMzFRISIrvdrpycHOOVIpjLz3/+cw0cOFDf//73tWLFCj377LPq2LGjOnXqpJUrV+raa68NdIm46MMPP9SCBQtUWFiobt266amnnlJycrK2bNnC882kPB6PXn75ZeXm5uqrr77STTfdpGeffVY333wz62ZS0dHR2rJli3HRc1Pr1NrHTEJQG/LVV1/pwIEDiouLU5cuXQJdDpqprKxMpaWlio+PV1hYWKDLQTPxfGubWLe2oal1as1jJiEIAABYEtcEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAQAASyIEAWiXPvzwQ6WmpiouLk7333+/jhw5IkkqLCzUfffdp4EDB2revHm65557lJOTI0natm2bRo4cqfj4eM2YMUNutzuQmwDAzwhBANqdmpoa/eQnP9GwYcO0efNmJSQkKDs7W5I0e/ZsjRgxQm+++aZyc3P17LPPatSoUfr73/+ujIwMTZgwQbm5ufr444+1ZMmSAG8JAH8iBAFol95++2398Ic/1LFjx3TmzBl9+umnkqRDhw7pnnvuUf/+/XXTTTfp2LFjioiI0Pr16/Uf//EfGjNmjPr27atx48Zp69atAd4KAP4UFOgCAOBKs9vtev3115Wbm6vIyEj17NlTNTU1kqTevXtr37596tKli/72t78Z31795Zdf6tChQ4qPj5ckVVdXq2PHjgHbBgD+RwgC0O68//77ys3N1fr163XNNdfoL3/5iw4cOCCPx6OoqChlZWVp5syZGj9+vPr37y9Juu666zRkyBBNmzZN0oW31M6dOxfIzQDgZ4QgAO2Oy+WSJJ05c0Z/+9vf9Nxzz8nj8ai0tFQffPCBVqxYoU6dOqlnz57GnNrrhP7+97/rpptu0quvvqoPP/xQa9asCdRmAPAzm8fj8QS6CAC4kiorK/Xzn/9cW7duVa9evfS9731Pzz//vP7yl7/ov//7v3Xs2DGdPXtWQUFBSk1N1Zw5cyRd+HTYwoULVVZWptjYWM2ZM0d9+/YN7MYA8BtCEADLWL16tTZu3KisrCxdddVVKioq0sSJE7Vjxw6Fh4cHujwArYy3wwBYxq233qp169bpvvvu0/nz53X99dcrMzOTAARYFK8EAQAAS+LvBAEAAEsiBAEAAEsiBAEAAEsiBAEAAEsiBAEAAEsiBAEAAEsiBAEAAEsiBAEAAEsiBAEAAEv6/xCIsIGd5YNaAAAAAElFTkSuQmCC"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 10
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-20T04:09:50.878246Z",
     "start_time": "2025-04-20T04:09:50.668814Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# 性别分布饼图\n",
    "gender_counts = data['gender'].value_counts()\n",
    "labels = gender_counts.index.astype(str)\n",
    "sizes = gender_counts.values\n",
    "plt.figure(figsize=(6, 6))\n",
    "plt.pie(sizes, labels=labels, autopct='%1.1f%%', startangle=140)\n",
    "plt.title('性别分布')\n",
    "plt.show()"
   ],
   "id": "8bbd0c87189c5907",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 11
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-20T04:09:52.824462Z",
     "start_time": "2025-04-20T04:09:50.878246Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# 消费分布直方图\n",
    "sns.histplot(data['price'])\n",
    "plt.title(\"消费分布\")\n",
    "plt.show()"
   ],
   "id": "8d20194fd46785e2",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/png": 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d6Lz194eWGGvfYJx9g3H2DX+Os88vjD548KDy8vLcn0NCQmSxWPTCCy+osLDQvf7w4cMKCgrSNddco4SEBB05csRddurUKdXV1Sk6OrpF2dGjRzVo0CBJarcsEDW/SLmq2qnzNf88BRUdZuvWhczN2wEAAH4IQcOGDdOmTZu0ceNGff7553r22Wd18803Kz4+Xs8995yKior0zjvvaNGiRZoyZYrCwsKUkpIiu92ugoICSdKaNWs0atQoWa1Wpaen6/3339e7774rp9OptWvXKi0tTZI0YcIE7dq1S+Xl5XI4HMrPz3eXBaKqaqeqqtsPK52pIzXOCHVlfVfrAADQ2/n8dNjAgQO1atUqLV26VHl5eUpLS9Py5cvVv39/nThxQo888oisVqsmTZqkOXPmNHYyOFhLlixRTk6Oli9frqCgIOXn50uS+vfvr9zcXM2cOVPh4eHq27evli1bJkkaMWKEZsyYoczMTIWGhmro0KGaNm2arw+5S7oaQFynuppzzRo1L3Otr6p2akj/8FbbbGtbAAAuJ365Jujmm2/W66+/3mJ9Tk6OcnJyWt0mIyNDe/bsUWlpqZKSktSvXz932dSpU5WWlqaTJ08qOTlZERER7rLHHntMkyZNct923/wC60DT1QBSVe2UjK6VVVU7Vemo0xVhbe+jvXYBALgc+O3C6O4YMGCAxowZ02pZTEyMYmJiWi2LjY1VbGysF3vWszoKID19uorTXwAAM+pVIQiNevp0Fae/AABmRAjqpXr6dBWnvwAAZuOXt8gDAAD4GyEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEu8OCwC8vBQAAN8jBAUAXl4KAIDvcToMAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYkt9C0Pnz5/XBBx/o3Llz/uoCAAAwMb+EoDfeeEPp6elasGCBbr31Vr3xxhuSpGPHjikzM1MpKSnKy8uTYRjubQ4ePKg77rhDqampWr9+vUd7u3fv1tixY5WWlqadO3d6lG3YsEGjRo1SRkaGioqKvH9wAACgV/B5CPrmm2/05JNP6ve//70KCwv1xBNPaMWKFaqrq9OsWbMUHx+vgoICVVRUaOvWrZKkyspKzZ49WxMnTtTGjRtVWFioAwcOSGoMTnPnzlV2drbWrVunVatW6eTJk5Kkt99+W3l5eXrqqae0YsUKLViwQGfPnvX1IQMAgADk8xBkt9s1f/58jRgxQpJ03XXX6ezZs9q/f7/sdrtyc3M1ZMgQzZkzR1u2bJEk7dixQwMHDtRDDz2kYcOGKTs72122efNmpaamKisrS3FxcZo+fbq2b98uSXrttdc0ZcoUjRs3TiNHjlRGRob27t3r60MGAAABKNjXO7zmmms0efJkSZLT6dTvfvc7jR8/XmVlZUpKSlJYWJgkKS4uThUVFZKk8vJypaamymKxSJISExO1cuVKSVJZWZlGjx7tbj8xMVGrV692l82dO9ej7NChQ8rKyupSn+vr67t5tO2351oahmR0tOypOt2ta/T8OHhb83GG9zDWvsE4+wbj7BveHOfOtunzEORSVlamH//4x7LZbNq1a5defPFFDR482F1usVgUFBSkc+fOyW63a/jw4e6yyMhInTlzRpLkcDg8tutsWVeUlJR0eZvOtmuz2eRwOBSiENVUOxUiW6tLu71W1RGWS67T3bqhClVpaamcTqdXxsKbvPX3h5YYa99gnH2DcfYNf46z30JQXFyc1q1bp2eeeUYLFixQTEyMQkJCPOqEhoaqtrZWVqvVo8y1XlK3y7oiISFBVqu1y9u1pb6+XiUlJe52I4qPKDzcpjo521xGGsEKDw+/5DrdrRsREaL4+PgeGwNfaD7O8B7G2jcYZ99gnH3Dm+PsarsjfgtBFotF3//+97Vs2TKNHz9ec+bM0fHjxz3qOBwO2Ww2RUdHq7KyssV6SR2WNb0QumlZV1itVq/8IrjatVgki9T+sqfqdLeuRb32y8Bbf39oibH2DcbZNxhn3/DnOPv8wuiDBw8qLy/P/TkkJEQWi0XDhw/XkSNH3OtPnTqluro6RUdHKyEhwaPs6NGjGjRokCR1WHb48OFWywAAgLn5PAQNGzZMmzZt0saNG/X555/r2Wef1c0336xbb71VdrtdBQUFkqQ1a9Zo1KhRslqtSk9P1/vvv693331XTqdTa9euVVpamiRpwoQJ2rVrl8rLy+VwOJSfn+9R9uqrr+r06dP66quvtGXLFncZAAAwN5+fDhs4cKBWrVqlpUuXKi8vT2lpaVq+fLmCg4O1ZMkS5eTkaPny5QoKClJ+fr4kqX///srNzdXMmTMVHh6uvn37atmyZZKkESNGaMaMGcrMzFRoaKiGDh2qadOmSZLS09O1e/du3XbbbZKkm266yf1nAABgbn65Jujmm2/W66+/3mJ9RkaG9uzZo9LSUiUlJalfv37usqlTpyotLU0nT55UcnKyIiIi3GWPPfaYJk2apNOnTyslJcV9MbTFYtGKFSt0//33q6amRjfccIP7NnsAAGBufrswui0DBgzQmDFjWi2LiYlRTExMq2WxsbGKjY1ttSwxMbGnugcAAC4TvEUeAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEIAACYEiEInWLxdwcAAOhhhCB0SnSYTfO3FWv+tmJ/dwUAgB4R7O8OoPeoqnb6uwsAAPQYZoIAAIAp+SUE7d27VxkZGbruuut01113qaKiQpK0ZMkSxcXFuf8ZP368e5tjx44pMzNTKSkpysvLk2EY7rKDBw/qjjvuUGpqqtavX++xr927d2vs2LFKS0vTzp07fXOAAAAg4Pk8BH3yySeaP3++cnJytH//fg0bNkyPP/64JOnDDz/Uyy+/rEOHDunQoUPatm2bJKmurk6zZs1SfHy8CgoKVFFRoa1bt0qSKisrNXv2bE2cOFEbN25UYWGhDhw4IKkxOM2dO1fZ2dlat26dVq1apZMnT/r6kAEAQADyeQiqqKhQTk6O7rzzTl111VWaOnWqPvroI128eFHHjx9XcnKyoqKiFBUVpcjISEnS/v37ZbfblZubqyFDhmjOnDnasmWLJGnHjh0aOHCgHnroIQ0bNkzZ2dnuss2bNys1NVVZWVmKi4vT9OnTtX37dl8fMgAACEA+vzB67NixHp8//vhjDR06VMeOHVNDQ4OmTJmi06dPKyUlRYsXL9a1116rsrIyJSUlKSwsTJIUFxfnPoVWXl6u1NRUWSyNN3EnJiZq5cqVkqSysjKNHj3ava/ExEStXr26y32ur6/v1rF21J5raRiS0dGyp+pcYl1vjIe3NB9neA9j7RuMs28wzr7hzXHubJt+vTusrq5O69ev1wMPPKATJ07o29/+thYuXKh+/frpmWee0cKFC7Vu3TrZ7XYNHjzYvZ3FYlFQUJDOnTsnu92u4cOHu8siIyN15swZSZLD4fDYrmlZV5SUlFzCUbbfrs1mk8PhUIhCVFPtVIhsrS7t9lpVR1guuc6l1m0wDJWWlsrp7D13innr7w8tMda+wTj7BuPsG/4cZ7+GoOeff15hYWHKysqSzWbT5MmT3WWLFi1SRkaG7Ha7rFarQkJCPLYNDQ1VbW1tizLXekntlnVFQkKCrFZrl7drS319vUpKStztRhQfUXi4TXVytrmMNIIVHh5+yXUuta4kxcfH99hYeFPzcYb3MNa+wTj7BuPsG94cZ1fbHfFbCCoqKtKGDRu0adMm2Wy2FuVXXnmlGhoadObMGUVHR+v48eMe5Q6HQzabTdHR0aqsrGyxXlK7ZV1htVq98ovgatdiaXwic7vLnqpziXVd/e5NvPX3h5YYa99gnH2DcfYNf46zX26RP3XqlHJycvTEE08oNjZWkpSXl6fCwkJ3ncOHDysoKEjXXHONEhISdOTIEY/t6+rqFB0d3aLs6NGjGjRokCS1WwYAAMzN5yGotrZWs2bNUkZGhsaPHy+HwyGHw6G4uDg999xzKioq0jvvvKNFixZpypQpCgsLU0pKiux2uwoKCiRJa9as0ahRo2S1WpWenq73339f7777rpxOp9auXau0tDRJ0oQJE7Rr1y6Vl5fL4XAoPz/fXQYAAMzN56fD3nnnHZ04cUInTpzQpk2b3Ov37dunO++8U4888oisVqsmTZqkOXPmNHYyOFhLlixRTk6Oli9frqCgIOXn50uS+vfvr9zcXM2cOVPh4eHq27evli1bJkkaMWKEZsyYoczMTIWGhmro0KGaNm2arw8ZAAAEIJ+HoHHjxqm8vLzVspycHOXk5LRalpGRoT179qi0tFRJSUnq16+fu2zq1KlKS0vTyZMnlZycrIiICHfZY489pkmTJrlvu29+gTUAADCnXvUC1QEDBmjMmDGtlsXExCgmJqbVstjYWPe1RwAAABIvUAUAACZFCAIAAKZECAIAAKZECAIAAKZECAIAAKZECAIAAKZECAIAAKZECIJXzd9WrPnbigOmHQAAXHrVwxLR+1RVOzus4wo3S+9OvKR2AADoCkIQ/K4nAs78bcWqqnbqinBbu2EKAAAXQhB8qq2wYrnEdquqnap01F1iKwAAMyEEwafaCivRYTbN31Ysi6SnmckBAPgAIQg95lJPSVVVO3XFP8KQ1P41Qm251BklAIB5EILQJe2FjJ46JXUp1whFNwlRiyfHX3JfAACXL0IQusQVMqL62HS+tjGsBNqFyNxJBgDoDEIQuqyq2ikZUlVN62GDU1IAgN6AEIQe13S2SCIUAQACEyEIl6StgOOaLZJahqL2tuuspqfkmrYLAEBnEYJwSVoLOK1pGoq6sl1TTYOTxyk5o81NAABoEyEIl6x5wPHWdt0JTgAAtIUQhF6lu4ELAIDmeIs8AAAwJUIQAhJ3lAEAvI3TYQhIrut/qqqdGtI/3N/dAQBchpgJQsByvYbjfBsPZQQA4FIQggAAgCkRggAAgCkRggAAgCkRggAAgCkRgnBZct1ib7PxdGkAQOsIQbgsRYfZtHB7qX5TXOPvrgAAAhTPCcJl62y1Uw7HBX93AwAQoJgJAgAApkQIAgAApkQIAgAApkQI8hPuWgIAwL+4MNpPflNcowvFRzT0Sl4OCgCAPxCC/KTScUEX1KB+4cwIAQDgD345HbZ3715lZGTouuuu01133aWKigpJ0rFjx5SZmamUlBTl5eXJMAz3NgcPHtQdd9yh1NRUrV+/3qO93bt3a+zYsUpLS9POnTs9yjZs2KBRo0YpIyNDRUVF3j84AADQK/g8BH3yySeaP3++cnJytH//fg0bNkyPP/646urqNGvWLMXHx6ugoEAVFRXaunWrJKmyslKzZ8/WxIkTtXHjRhUWFurAgQOSGoPT3LlzlZ2drXXr1mnVqlU6efKkJOntt99WXl6ennrqKa1YsUILFizQ2bNnfX3IAAAgAPk8BFVUVCgnJ0d33nmnrrrqKk2dOlUfffSR9u/fL7vdrtzcXA0ZMkRz5szRli1bJEk7duzQwIED9dBDD2nYsGHKzs52l23evFmpqanKyspSXFycpk+fru3bt0uSXnvtNU2ZMkXjxo3TyJEjlZGRob179/r6kAEAQADy+TVBY8eO9fj88ccfa+jQoSorK1NSUpLCwsIkSXFxce7TZOXl5UpNTZXF0vhGqMTERK1cuVKSVFZWptGjR7vbS0xM1OrVq91lc+fO9Sg7dOiQsrKyutTn+vr6Lh5lJ9szDBmNi46XPVUnEOr6aN/6x+nUnv77Q0uuMWasvYtx9g3G2Te8Oc6dbdOvF0bX1dVp/fr1euCBB/TJJ59o8ODB7jKLxaKgoCCdO3dOdrtdw4cPd5dFRkbqzJkzkiSHw+GxXWfLuqKkpKTL27THdXu83eFQdXWQaqqdCpGt3aXdXqvqCMsl1wmEuj7bd41TUmMYdjqdPfp3iNb19O8KWsc4+wbj7Bv+HOduhaBXXnlFDzzwgMezboqKirR69Wr9/ve/73Q7zz//vMLCwpSVlaXnnntOISEhHuWhoaGqra2V1Wr1KHOtl9Ttsq5ISEiQ1Wrt8nZtqa+vl4oOKDIiQuHh4aqTU+HhtnaXkUZwh3U7UycQ6vps30adHNXVGjFiRI/+/aGl+vp6lZSU9PjvCjwxzr7BOPuGN8fZ1XZHuhWCnn32WU2dOtUjBMXGxurIkSOdbqOoqEgbNmzQpk2bZLPZFB0drePHj3vUcTgc7rLKysoW6yV1WNb0QuimZV1htVq984tgscjSuOh42VN1AqGuj/atf5w+9drfH1pgrH2DcfYNxtk3/DnOXQpBhw4dkiQZhqH33ntP4eHh7s9/+ctf9J3vfKdT7Zw6dUo5OTl64oknFBsbK6lxtmXz5s0ederq6hQdHa2EhASPW9+PHj2qQYMGubc7cuSI+zqf5mWHDx/WTTfd1KIMAACYW5dC0Lx58yQ1Xq/zq1/9yn2hclBQkIYOHarly5d32EZtba1mzZqljIwMjR8/Xg6HQ5KUnJwsu92ugoICZWZmas2aNRo1apSsVqvS09P11FNP6d1331VKSorWrl2rtLQ0SdKECRM0depUzZgxQ4MHD1Z+fr4mT57sLlu0aJEyMzNltVq1ZcsWPf744105ZAAAcJnqUgh68803JUkjRoxQYWGhIiMju7zDd955RydOnNCJEye0adMm9/p9+/ZpyZIlysnJ0fLlyxUUFKT8/HxJUv/+/ZWbm6uZM2cqPDxcffv21bJly9x9mTFjhjIzMxUaGqqhQ4dq2rRpkqT09HTt3r1bt912myTppptucv8ZAACYW7euCUpLS1NwcPduLBs3bpzKy8tbLRs8eLD27Nmj0tJSJSUlqV+/fu6yqVOnKi0tTSdPnlRycrIiIiLcZY899pgmTZqk06dPKyUlxX0xtMVi0YoVK3T//ferpqZGN9xwg3v2CgAAmFu3kszatWt7uh9uAwYM0JgxY1oti4mJUUxMTKtlsbGx7uuLmktMTOyp7gEAgMtEt0LQ3r17tXTpUn3++efudYZhyGKx6KOPPuqxzgEAAHhLt0LQokWL9KMf/UiZmZnduuUcAADA37r9xOh//dd/bfPUFAAAQKDr1gtUH330US1evJg3sgMAgF6rWzNBO3bs0PHjxzV27Fh95zvf8bhV/j//8z97rHMAAADe0q0Q9KMf/ain+wEAAOBT3QpBd999d0/3AwAAwKe6FYJGjBjR5kMHuUUeAAD0Bt0KQfv27XP/uba2ViUlJVq3bp1mz57dYx0DAADwpm6FoG9961sen4cPH67Ro0dr1qxZuvPOO3ukYwAAAN7UrVvkWxMaGqqvvvqqp5oDAADwqm7NBN1///0e1wQZhqETJ07o5ptv7rGOAQAAeFOP3CJvsVg0aNAg3XjjjT3SKQAAAG+7pFvkv/76a3322Wf61re+pf79+/doxwAAALypWyHIbrdr3rx5evPNN2Wz2eR0OjV+/HgtXbrU4+nRAAAAgapbF0b/6le/UkNDg9566y0VFxfrrbfe0sWLF/WrX/2qh7sHAADgHd2aCXr77bdVUFCgQYMGSZIGDRqk3NxcZWZm9mjnAAAAvKVbM0HXXHONDhw44LHuwIEDuvbaa3ukU4A3zN9WrPnbiv3dDQBAgOjWTNDjjz+umTNn6o033lBMTIxOnTql999/X6+88kpP9w/oMVXVzg7ruELS0rsTvd0dAICfdWkmqKGhQYcPH1ZERITeeOMN3XDDDfrLX/6ilJQU7d69W8nJyd7qJ+ATVdXOToWltnRntokZKgDwj06HoPLyct1+++2aNWuW/vSnP+nqq6/Wz3/+c/Xp00cvv/yy7rvvPp04ccKbfQUCQnuhpa0Q1Z1tAADe1enTYQsXLlRWVpZ++tOfKijon9mpsLBQ9fX1+vWvf60FCxboD3/4g1c6CnhDd05/dRRYLK2sI+QAQODp9EzQ8ePHdfvtt3sEIBer1ap7771X5eXlPdo5wNtam4VpLcR0RXSYrVOnuOZvK9ayNz66xL0BALqr0zNBN910k5YuXaqnn366xdOhq6ur9fzzz2vkyJE93kHA11whpqraqSH9w3W+tjEk9eRskbuO0fjnSw1eAICu63QIWrp0qebNm6dbbrlFgwcP1pVXXimr1arz58/r448/1vDhw/XSSy95s69Al3U3XFRVO1XpqNMVYTZV1TjbbadpYOouV/CSuDMNAHyl0yHoiiuu0Jo1a/TJJ5/o8OHDOnPmjC5evKioqCiNGDFCI0eO9HizPBAIrogI0cLtpYoKs0nqfihyhZSoPrYWZU0DU3s62jfXDQGAb3X5OUFDhgzRkCFDvNEXwCvONgkXzU91dUVXT181r3Mp+wYA9LxuPSwR6M2az9x0Z3aovZmh9up0dtYIAOB9hCCYXmcCTWuazgxdSh0AgH8QggARVgDAjLr1AlUAAIDejhAEAABMiRAEAABMiRAEAABMiRAEAABMiRAEAABMiRAEAABMiRAEAABMyW8hqLKyUunp6fr000/d65YsWaK4uDj3P+PHj3eXHTt2TJmZmUpJSVFeXp4M459Ptjt48KDuuOMOpaamav369R772b17t8aOHau0tDTt3LnT+wcGAAB6Bb+EoMrKSs2aNUt///vfPdZ/+OGHevnll3Xo0CEdOnRI27ZtkyTV1dVp1qxZio+PV0FBgSoqKrR161Z3W7Nnz9bEiRO1ceNGFRYW6sCBA5Iag9PcuXOVnZ2tdevWadWqVTp58qRvDxYAAAQkv4SgOXPm6Ic//KHHuosXL+r48eNKTk5WVFSUoqKiFBkZKUnav3+/7Ha7cnNzNWTIEM2ZM0dbtmyRJO3YsUMDBw7UQw89pGHDhik7O9tdtnnzZqWmpiorK0txcXGaPn26tm/f7tuDBQAAAckv7w5bvHixYmJi9PTTT7vXHTt2TA0NDZoyZYpOnz6tlJQULV68WNdee63KysqUlJSksLAwSVJcXJwqKiokSeXl5UpNTZXF0vgu8MTERK1cuVKSVFZWptGjR7v3kZiYqNWrV3e5v/X19d0+1nbbMwwZjYuOlz1VJxDq+mjfMozGV8S3Ns4B1M+mS4+fj17E1efe2PfehHH2DcbZN7w5zp1t0y8hKCYmpsW6EydO6Nvf/rYWLlyofv366ZlnntHChQu1bt062e12DR482F3XYrEoKChI586dk91u1/Dhw91lkZGROnPmjCTJ4XB4bNe0rCtKSkq6vE17bLbGt5XbHQ5VVwepptqpENnaXdrttaqOsFxynUCo67N91zgVEm5TTU2NQiwXA7efTZYNhqHS0lI5nc4e/ZnzlZ7+XUHrGGffYJx9w5/jHDBvkZ88ebImT57s/rxo0SJlZGTIbrfLarUqJCTEo35oaKhqa2tblLnWS2q3rCsSEhJktVq7vF1b6uvrpaIDioyIUHh4uOrkVHi4rd1lpBHcYd3O1AmEuj7bt1En6aLCwsIUHh4SuP1sspSk+Pj4HvtZ85X6+nqVlJT0+O8KPDHOvsE4+4Y3x9nVdkcCJgQ1d+WVV6qhoUFnzpxRdHS0jh8/7lHucDhks9kUHR2tysrKFusltVvWFVar1Tu/CBaLLI2Ljpc9VScQ6vpo3/rHKdJWxzmA+tl0KalXf+l67XcFHhhn32CcfcOf4xwwzwnKy8tTYWGh+/Phw4cVFBSka665RgkJCTpy5Ii77NSpU6qrq1N0dHSLsqNHj2rQoEGS1G4ZAAAwt4AJQSNGjNBzzz2noqIivfPOO1q0aJGmTJmisLAwpaSkyG63q6CgQJK0Zs0ajRo1SlarVenp6Xr//ff17rvvyul0au3atUpLS5MkTZgwQbt27VJ5ebkcDofy8/PdZQAAwNwC5nTYXXfdpRMnTuiRRx6R1WrVpEmTNGfOHElScHCwlixZopycHC1fvlxBQUHKz8+XJPXv31+5ubmaOXOmwsPD1bdvXy1btkxSY7CaMWOGMjMzFRoaqqFDh2ratGl+O0YAABA4/BqCysvLPT7n5OQoJyen1boZGRnas2ePSktLlZSUpH79+rnLpk6dqrS0NJ08eVLJycmKiIhwlz322GOaNGmS+7b75hdYAwAAcwqYmaDOGDBggMaMGdNqWUxMTKu33ktSbGysYmNjvdgzAADQ2wTMNUEAAAC+RAgCAACmRAgCAACmRAgCAACmRAgCAACmRAgCAACmRAgCAACmRAgC4DZ/W7Hmbyv2dzcAwCd61cMSAbNzBZSldyd6ZZuqaqdX+wIAgYQQBAQQSwflXQkpTbdp3m5PBJju9AUAAgkhCAgg0WG2bgeU+duKZZH0dCvbudqtqnZqSP9wAgwAiBAEBJyunpJqGmyu+EfYiepj0/lap6L62DzarXTU6YowWzstdjwbBQCXC0IQEIBaO33lCjRNy1oLNlXVTsmQqmoal13VdNboinCbe0aqvZkmAOiNCEFAAGr19JXhWdZ0lqenucJV83VX+GDfAOArhCAgQLV3+qppKPKm1k6N+WrfAOBthCAAbfLFrBMA+AshCEC7mPkBcLkiBAEm1fRUF7M9AMyIEASYVNNTXcz2ADAjQhBgYoQfAGbGC1QBAIApEYIAAIApEYIAAIApEYIAAIApEYIAAIApEYIAAIApEYIAAIApEYIAdFvTp07bbDxxGkDvwsMSAXSb66nTZx1OheqiVsb7u0cA0HmEIACXpKraqUpHnULl9HdXAKBLOB0GAABMiRAEAABMiRAEAABMiRAEAABMiRAEAABMiRAEAABMiRAEAABMiRAEwKfmbyvW/G3F/u4GAPgvBFVWVio9PV2ffvqpe92xY8eUmZmplJQU5eXlyTAMd9nBgwd1xx13KDU1VevXr/doa/fu3Ro7dqzS0tK0c+dOj7INGzZo1KhRysjIUFFRkXcPCkCHqqqdqqr2/YMV528rVvaG9whgANz8EoIqKys1a9Ys/f3vf3evq6ur06xZsxQfH6+CggJVVFRo69at7vqzZ8/WxIkTtXHjRhUWFurAgQOSGoPT3LlzlZ2drXXr1mnVqlU6efKkJOntt99WXl6ennrqKa1YsUILFizQ2bNnfX/AADxYOq4iqWdnjVxPtvZHAAMQmPwSgubMmaMf/vCHHuv2798vu92u3NxcDRkyRHPmzNGWLVskSTt27NDAgQP10EMPadiwYcrOznaXbd68WampqcrKylJcXJymT5+u7du3S5Jee+01TZkyRePGjdPIkSOVkZGhvXv3+vZgAbhnYZa98ZGkf75zrKOA05VZo/nbivU4szwAusAv7w5bvHixYmJi9PTTT7vXlZWVKSkpSWFhYZKkuLg4VVRUSJLKy8uVmpoqi6Xx/x8TExO1cuVK93ajR492t5OYmKjVq1e7y+bOnetRdujQIWVlZXWpv/X19d04yk60ZxgyGhcdL3uqTiDU9dG+ZRiNUw6tjXMA9bO3jGd7SxmGLJa2f1fOOhpnYaLDbO7tqhxOWdRym4XbS3W22qmhV4bLdUa8tToWSU/d9c83tp51OHVFuE3ztzYGocV3eb7N1X1MRs//TvuKq9+9tf+9BePsG94c58626ZcQFBMT02Kd3W7X4MGD3Z8tFouCgoJ07tw52e12DR8+3F0WGRmpM2fOSJIcDofHdp0t64qSkpIub9Mem80mSbI7HKquDlJNtVMhsrW7tNtrVR1hueQ6gVDXZ/uucSok3KaamhqFWC4Gbj97y3i2V9dRq6sH9dW/bz4iwzA08/ooSdKa984rOjxENdXVrbYXHW7TL//wnhoMQz9JbPwfoE+/rNLX9gsKkVM11U4ZhqFjx47J6XS6f38+/bJK/SJC9Ms/vKev7LX69oC+qqmuVohsOtdkm9b6EKpQlZaWutvrjXr6OwmtY5x9w5/jHDBvkbdarQoJCfFYFxoaqtra2hZlrvWtbdfZsq5ISEiQ1Wrt8nZtqa+vl4oOKDIiQuHh4aqTU+HhtnaXkUZwh3U7UycQ6vps30adpIsKCwtTeHhI4Pazt4xne3UbGn8/ahqCdEVEiPI/cioqzKYLCladrAoLD2+zvarqxhmh+PjGmZuI4iO6IJu77hXhNnd752ucigqTIiIi3NtekM29D1e7Tbdp3oeIiBD3vnqb+vp6lZSU9Ph3Ejwxzr7hzXF2td2RgAlB0dHROn78uMc6h8Mhm82m6OhoVVZWtljv2q69sqYXQjct6wqr1eqdXwSLRZbGRcfLnqoTCHV9tG/94/Rpq+McQP3sLePZ3rL5WFfVOF0fO9XeFWE2LdxRqqg+tlbrutrrSrtt1rWo1/+HzWvfSfDAOPuGP8c5YJ4TlJCQoCNHjrg/nzp1SnV1dYqOjm5RdvToUQ0aNKjV7ZqXHT58uNUyAIGlqtqp8zXeP0Vl8foeAPQWAROCUlJSZLfbVVBQIElas2aNRo0aJavVqvT0dL3//vt699135XQ6tXbtWqWlpUmSJkyYoF27dqm8vFwOh0P5+fkeZa+++qpOnz6tr776Slu2bHGXATCnzt6ZBuDyFzCnw4KDg7VkyRLl5ORo+fLlCgoKUn5+viSpf//+ys3N1cyZMxUeHq6+fftq2bJlkqQRI0ZoxowZyszMVGhoqIYOHapp06ZJktLT07V7927ddtttkqSbbrrJ/WcA5sWzggBIfg5B5eXlHp8zMjK0Z88elZaWKikpSf369XOXTZ06VWlpaTp58qSSk5MVERHhLnvsscc0adIknT59WikpKe6LoS0Wi1asWKH7779fNTU1uuGGG9y32QMAAHMLmJkglwEDBmjMmDGtlsXExLR6e70kxcbGKjY2ttWyxMTEnuoeAAC4TATMNUEAAAC+RAgCAACmRAgCAACmRAgCAACmRAgCAACmRAgCAACmRAgCAACmRAgCAACmRAgCAACmRAgCAACmRAgCAACmRAgCYEr+fpXy/G3Fmr+t+JLrAOi+gHuBKgD4QnSYzR0wlt7d+JLl+duKVVXt1BXhNve65ppv011V1c4O221eB0DPIgQBMK3mIaOq2qlKR12XtvFWXwB4HyEIANrREzM/rhmmfuE2Pd1OO/4+RQeYDSEIgKl1FDx6YobGNcN0xT9OwUX1sbVaz3WKrqraqSH9wy95vwDaRwgCYGrRHQST1nQUnFztna91tmi3qtopGW1v2zQwdWZfALqPEATA9JoHk46CR9MZm6YXUbvCj6u9qpr2A09nAk7TC7gXT47vxBYAOosQBADNNJ8dai2suGZsLM3WtRd6OtpPW7hoGvAOQhAAtKJpoGkvrHTndFpb+wHgW4QgAOiE9sIKQQbonXhiNAAAMCVCEAAAMCVCEAAAMCVCEAAAMCVCEAAAMCVCEAD0Aq7nEdls3bsVH0BLhCAA6AWiw2xauL1Uvymu8XdXgMsGzwkCgF7ibLVTDscFf3cDuGwwEwQAJjN/W7H7fWSAmTETBAAmw7vIgEbMBAFAL8asDtB9zAQBQC/m7VkdV8BaeneiV/cD+AMhCADQps6ELIISeitCEACYkKXJny81xDQPSoQi9BaEIAC4jHQ2gESH2TR/W7Gi+thUVe30CEUdtW+R9HQ77XPhNXoLQhAA9CKthZWm65oHmvnbilVV7dQV4bYWwaiq2ikZjX92haKqaqf6hds8Qk7z9q9oUndI//A2+wUEOkIQAPQiV0SEaOH2UlXV/DOANJ3Vaf65qtqpSkddp9p21b2infZaq9tWHSDQBdwt8kuWLFFcXJz7n/Hjx0uSjh07pszMTKWkpCgvL0+GYbi3OXjwoO644w6lpqZq/fr1Hu3t3r1bY8eOVVpamnbu3OnTYwEAbzj7jwByvuafp52qqp3tfu6q7rR3qfsEfC3gQtCHH36ol19+WYcOHdKhQ4e0bds21dXVadasWYqPj1dBQYEqKiq0detWSVJlZaVmz56tiRMnauPGjSosLNSBAwckNQanuXPnKjs7W+vWrdOqVat08uRJfx4eAPiFr09XcXoMvUFAhaCLFy/q+PHjSk5OVlRUlKKiohQZGan9+/fLbrcrNzdXQ4YM0Zw5c7RlyxZJ0o4dOzRw4EA99NBDGjZsmLKzs91lmzdvVmpqqrKyshQXF6fp06dr+/bt/jxEAPAL1+mqZW985NP9ZW94j4c5ImAF1DVBx44dU0NDg6ZMmaLTp08rJSVFixcvVllZmZKSkhQWFiZJiouLU0VFhSSpvLxcqampslga/78jMTFRK1eulCSVlZVp9OjR7vYTExO1evXqLvervr7+Ug+t9fYMQ0bjouNlT9UJhLo+2rcMo/F/R1sb5wDqZ28Zz/aWjf+ytD7WAdTPgN93B3U9fqa70V6Vw9lxX3rwmKocjaftDKPnv0e9ydXX3tTn3sib49zZNgMqBJ04cULf/va3tXDhQvXr10/PPPOMFi5cqO9+97saPHiwu57FYlFQUJDOnTsnu92u4cOHu8siIyN15swZSZLD4fDYrmlZV5SUlFzCUbVkszVeOGh3OFRdHaSaaqdCZGt3abfXqjrCcsl1AqGuz/Zd41RIuE01NTUKsVwM3H72lvFsr66jVors2+pYB1Q/e8t4tlW3yc90QPezWZ1Qhaq0tFROZ++6Xqinv/vROn+Oc0CFoMmTJ2vy5Mnuz4sWLVJGRoaGDx+ukJAQj7qhoaGqra2V1Wr1KHOtl9RuWVckJCTIarV2ebu21NfXS0UHFBkRofDwcNXJqfBwW7vLSCO4w7qdqRMIdX22b6NO0kWFhYUpPDwkcPvZW8azvboNjb8frY11QPWzt4xnW3Wb/EwHdD+b1YmICFF8fHyPfYd6W319vUpKSnr8ux+evDnOrrY7ElAhqLkrr7xSDQ0Nuuqqq3T8+HGPMofDIZvNpujoaFVWVrZYL6ndsq6wWq3e+UWwWGRpXHS87Kk6gVDXR/vWP06RtjrOAdTP3jKe7S3bHesA6mfA77uDuh7jHMD9bFHHol4ZJrz23Q8P/hzngLowOi8vT4WFhe7Phw8fVlBQkOLi4nTkyBH3+lOnTqmurk7R0dFKSEjwKDt69KgGDRokSe2WAQAAcwuoEDRixAg999xzKioq0jvvvKNFixZpypQpuvnmm2W321VQUCBJWrNmjUaNGiWr1ar09HS9//77evfdd+V0OrV27VqlpaVJkiZMmKBdu3apvLxcDodD+fn57jIAAGBuAXU67K677tKJEyf0yCOPyGq1atKkSZozZ46Cg4O1ZMkS5eTkaPny5QoKClJ+fr4kqX///srNzdXMmTMVHh6uvn37atmyZZIaQ9WMGTOUmZmp0NBQDR06VNOmTfPnIQIAuokXs6KnBVQIkqScnBzl5OS0WJ+RkaE9e/aotLRUSUlJ6tevn7ts6tSpSktL08mTJ5WcnKyIiAh32WOPPaZJkya5b7lvfoE1AKB36M6LWdt7dxoQcCGoPQMGDNCYMWNaLYuJiVFMTEyrZbGxsYqNjfVizwAAbbH4cd9deXcazCegrgkCAFx+XE+P5snRCDS9aiYIANA7NT+V5Xrj/PnaxvWdPVXVfFap+XVC87cVyyLp6S6c+nKdMhvSP7yxP4Z0X2zXH6eC3ocQBADwuarqxrBRVeNs83RZaxdCu2aVXKGlebiqqnbqin/UierTuSDjOmV2RZhNVTWNrxaRCEFmQAgCAPhEW2GnebA5X+tUVB9bmxdCNw0tbbXrClmt7bs7s0W4PBGCAAA+Ed3ODE3z2RhXgOnMRdXttdtane7MFuHyRAgCAPhM8xmajnQm4HS23eZ1utoXXH4IQQCAgEZYgbdwizwAADAlQhAAADAlQhAAADAlQhAAADAlQhAAAE1YJNls3DpvBoQgAACaiA636ZX3v9HC7aX+7gq8jFvkAQBoptJxQWGG1d/dgJcxEwQAAEyJmSAAADrQ2stcO6rjeh/aFeE2j3XN6zRvtzP7Qs8gBAEA0Iqm7y1r7WWuzcNKa2+0r3TUtVjX/HPz96O1tq61ffMS2EtHCAIAoBXR4e2/t6y1sNJaeOmojuv9aFXVTg3pH+6xLqqPTedrnS0CT9OXwErMGnUXIQgAgDZ09N6y5i94be2Fr52p45o1uiLMc50Mqarmn4GnaVBy10G3EYIAAOiEtk5Rdebt9D3xBvvWglJ7/ULHCEEAAHRCa6etAkE0p8W6jRAEAEAntTUb42+cFusenhMEAABMiRAEAABMiRAEAABMiRAEAABMiRAEAABMiRAEAABMiRAEAABMiecEAQBwGQiUl666HijZL9zW5r7mbyuWDOm+WP8+b4kQBADAZaCjJ0c3femq68WsrqXrKdhN17W1bB5wmrfX9IGSre3LVccwJIkQBAAAekBrb7Zv7WWtrhezupau0NJ0XVvL5gGneXvN+9NaO4GCEAQAwGWk+TvOuvOy1s7wVru+xIXRAABcZlynpM7X8E6x9hCCAACAKRGCAACAKRGCAACAKZkiBB07dkyZmZlKSUlRXl6eDKOXX8kFAAAu2WUfgurq6jRr1izFx8eroKBAFRUV2rp1q7+7BQAA/OyyD0H79++X3W5Xbm6uhgwZojlz5mjLli3+7hYAAPCzyz4ElZWVKSkpSWFhYZKkuLg4VVRU+LlXAADA3y77hyXa7XYNHjzY/dlisSgoKEjnzp1TdHR0u9u6rh2qq6uT1WrtsT7V19drUN9QXTCs6hcerGCLob5h7S+DLeqwbmfqBEJdn+1bhmwWi5yGVX3DA7ifvWU826srQ1eFB7U61gHVz94ynm3VbfIzbQsK4H4GyL673c8+warvG6r+YcGyBXI/e8t4tlFHRuN/Z3v6v7Gu/85K6vAaYItxmV8lvGLFCl28eFG5ubnudbfeeqs2bdqkQYMGtbttXV2dSkpKvN1FAADgBQkJCQoJCWmz/LKfCYqOjtbx48c91jkcDtlsHb+0LTg4WAkJCQoKCpLF0tH7eQEAQCAwDEMNDQ0KDm4/5lz2ISghIUGbN292fz516pTq6uo6PBUmSUFBQe0mSAAA0Htd9hdGp6SkyG63q6CgQJK0Zs0ajRo1qsfPPwIAgN7lsr8mSJL27dunnJwchYaGKigoSPn5+YqNjfV3twAAgB+ZIgRJ0pdffqnS0lIlJSWpX79+/u4OAADwM9OEIAAAgKYu+2uCAAAAWkMIAgAApkQIAgAApkQI8rFjx44pMzNTKSkpysvL6/CR3vC0d+9eZWRk6LrrrtNdd93lfg9ce+N68OBB3XHHHUpNTdX69es92tu9e7fGjh2rtLQ07dy506fH0lv89Kc/1datWyV1fyw3bNigUaNGKSMjQ0VFRT7re2+yYsUKzZo1y/2Zn+metXnzZt16661KSkrS/fffr1OnTklinHtCZWWl0tPT9emnn7rXeWNcvfI9YsBnLly4YIwdO9ZYuHCh8be//c148MEHjS1btvi7W73G3/72NyMlJcV4/fXXjS+//NL4xS9+Ydx7773tjuvXX39tjBw50nj++eeNjz/+2Lj77ruNoqIiwzAMo7y83IiPjzc2bdpklJWVGePHjzcqKir8eYgBZ/v27cb3vvc9o6CgoNtjuX//fiMhIcHYs2eP8d577xnp6elGZWWlPw8r4Hz00UfGD37wA+OTTz4xDKP97wp+prvub3/7m3HrrbcaH374ofH3v//dyM3NNaZNm8Y494Cvv/7ayMrKMr73ve8Zp06dMgzDOz+/3voeIQT50J49e4yUlBSjurraMIzGL7777rvPz73qPd58803jD3/4g/tzUVGRkZiY2O64rl+/3rj99tuNhoYGwzAa/w5ycnIMwzCMJUuWGD/5yU/c7f32t781nn32WV8dTsA7e/asMWrUKGPChAlGQUFBt8dy9uzZxsKFC91lTz/9tLFp0yYfHklgq6+vN7KysoznnnvOvY6f6Z71xhtvGL/4xS/cn//6178aN998M+PcA3784x8bv/vd7zxCkDfG1VvfI5wO86GysjIlJSUpLCxMkhQXF+c+nYOOjR07Vvfee6/788cff6yhQ4e2O67l5eVKTU11v/stMTFRpaWlkhr/Pm688UZ3e03LIOXl5WncuHH6wQ9+IKn7Y9la2Ycffuijowh8r732mo4dO6Zvfetb2rdvn+rq6viZ7mGxsbE6cOCAPvroI33zzTd69dVXdfPNNzPOPWDx4sWaMWOGxzpvjKu3vkcIQT5kt9s1ePBg92eLxaKgoCCdO3fOj73qnerq6rR+/Xrdd9997Y5r87LIyEidOXNGUuOLdNsqM7sDBw6oqKhIv/zlL93rujuWjHPbHA6Hnn/+ecXExOizzz7Tb3/7W02bNo2f6R4WGxurCRMmaMqUKUpOTtaRI0c0b948xrkHxMTEtFjnjXH11pgTgnzIarW2eCFraGioamtr/dSj3uv5559XWFiYsrKy2h3X5mVNx7u9MjO7cOGCFi1apF/96leKjIx0r+/uWDLObduzZ49qamr0u9/9Tr/4xS+0fv16ORwOFRQU8DPdg4qLi/WnP/1JmzZt0l//+lf98Ic/1IMPPsh3h5d4Y1y9NeaEIB+Kjo5WZWWlxzqHwyGbzeanHvVORUVF2rBhg1auXCmbzdbuuDYvazre7ZWZ2Ysvvqjvf//7GjNmjMf67o5ldHS0zp4922qZ2X3xxRdKSkpS//79JUnBwcGKi4vT+fPn+ZnuQTt37tTEiROVlJSkvn376tFHH9WpU6f47vASb4yrt75HCEE+lJCQoCNHjrg/nzp1SnV1dYqOjvZfp3qZU6dOKScnR0888YT7JbjtjWvzsqNHj2rQoEGtbte0zMwKCwv15ptvKjk5WcnJydq5c6eefPJJ/fGPf+zWWCYkJOjw4cOtlpnd1VdfrQsXLnis++yzzzR//nx+pntQQ0ODvv76a/dnh8OhmpoaBQcHM85e4I3vZG99jxCCfCglJUV2u10FBQWSpDVr1mjUqFGyWq1+7lnvUFtbq1mzZikjI0Pjx4+Xw+GQw+FQcnJym+Oanp6u999/X++++66cTqfWrl2rtLQ0SdKECRO0a9culZeXy+FwKD8/311mZq+++qoKCwv1xz/+UX/84x+Vnp6uX/ziF/rTn/7UrbGcMGGCXn31VZ0+fVpfffWVtmzZwjj/w6233qoTJ07otdde0xdffKH//M//VFlZmW677TZ+pntQcnKy9uzZo9/+9rcqLCxUdna2BgwYoPvvv59x9oL2/lvX3XH12vfIJd9fhi7Zu3evkZSUZNxwww3GjTfeaBw/ftzfXeo19uzZY3zve99r8c+pU6faHddXX33ViI+PN1JSUoz09HTjyy+/dJc9++yzRnx8vDFy5Ejj7rvvNmpqavxxaAFt3rx5RkFBgWEY3RvLhoYGY+7cuUZiYqKRmJho/PznP3ffHovG27X/9V//1UhMTDQyMjKMffv2GYbR/ncFP9Nd09DQYLzwwgvGmDFjjPj4eGPKlClGaWmpYRiMc09peou8YfT8uHrre4S3yPvBl19+qdLSUiUlJalfv37+7s5lo71xPXXqlE6ePKnk5GRFRER4lJ04cUKnT59WSkpKi4v50FJ3x7K4uFg1NTW64YYb3LfHon38TPsG4+wd3hjXnv4eIQQBAABT4pogAABgSoQgAABgSoQgAABgSoQgAABgSoQgAABgSoQgAKbz6aefKi4uzt/dAOBn3CIPwHQaGhpkt9sVFRXl764A8CNCEAAAMCVOhwHolbZu3ap77rlHs2fP1vXXX6+f/vSnOnPmjCTp3//93/X8889r+/bt7ncONdXW6bCjR4/q3nvv1b/8y7/ovvvu0/Hjx91lxcXFysrK0vXXX6+HH35Y33zzjXcPEIDXEYIA9FolJSX6l3/5F/3xj39USEiIFi1a5C575513tGHDBs2bN08ZGRkdtvXNN9/oZz/7mW699Vbt3r1bCQkJmjt3riTp/PnzevDBBzV69Gjt2LFDdrtdy5Yt89pxAfCNYH93AAC66+qrr9aDDz4oi8WiRx55RPfcc48uXrwoSfrkk0/03//93+rbt2+n2nrrrbcUFRWl7OxsSdLDDz+sv/zlL+4ym82mhx9+WBaLRT/5yU80b9487xwUAJ8hBAHota6++mr3SxQHDRqk+vp6VVVVSZKmTJnS6QAkSZ9//rkGDx7s/hwdHa0777xTkvTFF1+osrJSKSkpkhovrHY4HLpw4YJCQ0N76GgA+BohCECv9dlnn8kwDFksFn3++ecKDg52v606PDy8S21dc801+vvf/+7+7HA4dO+992r9+vW6+uqrFR8fr1//+teSJMMwZLfbFRzMVyjQm3FNEIBe68yZM1qzZo1OnTqlF154QRkZGbJard1qa8yYMTp37pzWrFmjL774Qi+99JLq6+t11VVXacyYMfr8889VXFysPn366L/+67/0s5/9TNxcC/RuhCAAvdYPfvADFRcXa9KkSXI6nVq4cGG32+rbt6/Wrl2rN998U3fccYc++OADvfDCC7JYLIqKitKLL76o9evXa9y4cdq9e7deeuklZoKAXo7nBAHolbZu3apt27YpPz/f310B0EsxEwQAAEyJmSAAAGBKzAQBAABTIgQBAABTIgQBAABTIgQBAABTIgQBAABTIgQBAABTIgQBAABTIgQBAABTIgQBAABT+v+f/kpOzL/30AAAAABJRU5ErkJggg=="
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 12
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-20T04:09:53.144321Z",
     "start_time": "2025-04-20T04:09:52.824462Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# 年龄段 vs 平均消费（分箱 + 分组）\n",
    "# 年龄分段\n",
    "data['age_bin'] = pd.cut(data['age'], bins=[15, 25, 35, 45, 55, 65, 100])\n",
    "\n",
    "# 分组后平均价格\n",
    "age_price = data.groupby('age_bin')['price'].mean().reset_index()\n",
    "\n",
    "sns.barplot(x='age_bin', y='price', data=age_price)\n",
    "plt.xticks(rotation=30)\n",
    "plt.title(\"不同年龄段的平均消费\")\n",
    "plt.show()\n",
    "data.drop(['age_bin'], axis=1, inplace=True)"
   ],
   "id": "875a034ec4bb4bea",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 13
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-20T04:09:53.520428Z",
     "start_time": "2025-04-20T04:09:53.144321Z"
    }
   },
   "cell_type": "code",
   "source": [
    "corr = data[['age', 'income', 'credit_score', 'price', 'items']].corr()\n",
    "sns.heatmap(corr, annot=True, cmap='coolwarm')\n",
    "plt.title(\"变量相关性\")\n",
    "plt.show()"
   ],
   "id": "3c99846c031fa79f",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 14
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-20T04:09:57.788149Z",
     "start_time": "2025-04-20T04:09:53.520428Z"
    }
   },
   "cell_type": "code",
   "source": [
    "sns.scatterplot(x='age', y='credit_score', data=data)\n",
    "plt.title(\"年龄与信用分数关系\")\n",
    "plt.show()"
   ],
   "id": "acff75235afa2b59",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 15
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-20T04:09:58.177998Z",
     "start_time": "2025-04-20T04:09:57.788149Z"
    }
   },
   "cell_type": "code",
   "source": [
    "features = data[['income', 'credit_score', 'price', 'items']].copy()\n",
    "# 标准化\n",
    "scaler = MinMaxScaler()\n",
    "scaled = scaler.fit_transform(features)\n",
    "\n",
    "# 添加得分列（简单平均得分）\n",
    "data['value_score'] = scaled.mean(axis=1)\n",
    "\n",
    "# 找出高价值用户（前1%）\n",
    "threshold = data['value_score'].quantile(0.99)\n",
    "# sns.boxplot(x='gender', y='value_score', data=data)\n",
    "high_value_users = data[data['value_score'] >= threshold].sort_values('value_score', ascending=False)\n",
    "data.drop(['value_score'], axis=1, inplace=True)\n",
    "high_value_users.head(10)"
   ],
   "id": "2bbaa5bd83c43a19",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "          user_name chinese_name  age     income gender  credit_score  \\\n",
       "1811847      yqhcrl          宋梓涵   99   993000.0      男           839   \n",
       "1857206    hhezryio          钟梓涵   99   992000.0      女           840   \n",
       "2220769  jvujshmhwz          汤梓涵  100   992000.0      男           850   \n",
       "920564      davxxvn          沈梓涵   98   991000.0      女           837   \n",
       "1746466     bmqtzzp          傅欣怡   99   967000.0      女           843   \n",
       "471975    gipxoqmqp          史梓涵  100   985000.0      男           849   \n",
       "463711      wkhcykq          卢梓涵  100  1000000.0      女           846   \n",
       "345860    tzfoaatfo          侯梓涵   98  1000000.0      女           831   \n",
       "359690   gvdguzxyzz          漕欣怡  100   959000.0      男           850   \n",
       "212800    BWJMPYNRR           陆明  100   982000.0      女           850   \n",
       "\n",
       "           price  items  value_score  \n",
       "1811847   9901.0     10     0.990773  \n",
       "1857206   9881.2     10     0.990482  \n",
       "2220769   9693.1     10     0.990320  \n",
       "920564    9891.1     10     0.989116  \n",
       "1746466  10000.0     10     0.988568  \n",
       "471975    9673.3     10     0.987620  \n",
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     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 16
  },
  {
   "metadata": {
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     "end_time": "2025-04-20T04:09:58.270478Z",
     "start_time": "2025-04-20T04:09:58.177998Z"
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   },
   "cell_type": "code",
   "source": [
    "young_high_credit_low_active = data[\n",
    "    (data['age'] <= 30) &\n",
    "    (data['income'] >= data['income'].quantile(0.75)) &\n",
    "    (data['items'] <= data['items'].quantile(0.25))\n",
    "]\n",
    "young_high_credit_low_active.head(10)"
   ],
   "id": "b54a95d83d6a3154",
   "outputs": [
    {
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      "text/plain": [
       "      user_name chinese_name  age     income gender  credit_score    price  \\\n",
       "184     hqzurif          蔡梓萱   20   869000.0      男           318   401.05   \n",
       "261     foayoag          贾欣怡   27   962000.0      男           361   554.50   \n",
       "291      gutjda           冯浩   19   971000.0      女           313   309.97   \n",
       "307      uewfxs          董梓涵   23  1000000.0      男           337   417.98   \n",
       "368  cfouskgwhm           贺思   28   898000.0      男           370  2352.54   \n",
       "555   auoewhyfk           白欣   19   933000.0      女           311   510.94   \n",
       "559       rylew          徐梓萱   30   878000.0      男           383  2257.50   \n",
       "675     rybfwyy          曾梓萱   19   873000.0      男           306  1690.23   \n",
       "749  vbgewarfbb           文思   22   892000.0      女           332  1007.13   \n",
       "825    sgyrmedc           谭涵   18   795000.0      男           304   198.20   \n",
       "\n",
       "     items  \n",
       "184      1  \n",
       "261      1  \n",
       "291      1  \n",
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       "559      3  \n",
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     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
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   "execution_count": 17
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   "source": "",
   "id": "4f636996ae722b6f",
   "outputs": [],
   "execution_count": 17
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